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Fu H (2023), "Pedestrian inertial navigation dataset with wearable sensor" Recherche Data Gouv.
Abstract: This pedestrian inertial navigation dataset contains 6 realistic tracks collected by two volunteers in diverse environments (campus, office building, city, woods, and parking lot in a shopping mall), totaling over 2 km walking distance.
The data are recorded with “ULISS”, a device developed by laboratory GEOLOC, a state-of-the-art inertial navigation system enclosing an Xsens Mit-7 IMU-Mag sensor, an atmospheric pressure sensor BMP280, and a dual frequency GNSS receiver, providing acceleration, angular rate, magnetic field, atmospheric pressure, and temperature readings at 200Hz, GNSS reading at 5Hz, using GPS timestamps. A detailed description of the device is available: https://geoloc.univ-gustave-eiffel.fr/en/hardware/geolocation-of-travelers.
During the experiment, the volunteer holds one ULISS horizontally (the z-axis points to the sky, see the photo), and walks naturally. The other ULISS is attached to his foot as the reference tracker and provides the ground truth trajectory and stride instants. All tracks started with a 40-second static phase in an outdoor environment.
Each track contains the following elements: - Raw data recorded by the handheld ULISS device including acceleration, angular rate, magnetic field, atmospheric pressure, temperature, and GNSS.
- Magnetometer calibration parameters of the handheld device
- Allan variance calibration parameters of the handheld device
- Ground Truth user trajectory and stride instants given by the foot-mounted ULISS. English (2023)
BibTeX:
@dataset{Fu2023a,
  author = {Fu, Hanyuan},
  title = {Pedestrian inertial navigation dataset with wearable sensor},
  publisher = {Recherche Data Gouv},
  year = {2023},
  url = {https://entrepot.recherche.data.gouv.fr/dataset.xhtml?persistentId=doi:10.57745/ZCBIIB},
  doi = {10.57745/ZCBIIB}
}
Zhu N, Bouronopoulos A, Leduc T, Servières M and Renaudin V (2023), "Evaluation of the Human Body Mask Effects on GNSS Wearable Devices for Outdoor Pedestrian Navigation Using Fisheye Sky Views", In 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)., April, 2023. , pp. 10p.. IEEE.
Abstract: An increasing number of Global Navigation Satellite Systems (GNSS)-based wearable devices emerged in our daily life in recent years. The utilities of these wearable devices vary from entertainment applications to safety and reliability-critical applications (such as blind people guidance, health monitoring, behavior-based soft mobility insurance, etc.). A key challenge for safety and reliability-critical applications using GNSS is the tracking of reliable and high quality signals in stringent environments. One particularity for wearable devices compared to other GNSS devices is that GNSS signals can be masked by not only the surrounding obstacles but also by the body of the users. Many research work addresses the impact of the surrounding obstacles on GNSS signal receptions whereas very few research studies the impact of human body mask. The objective of this paper is to investigate the impact of the user body mask on wearable GNSS devices. By fixing a fisheye camera on GNSS wearable devices on two body parts of a pedestrian, i.e., hand and foot, the sky view representing the “point of view” of the device can be obtained. The images are first segmented to distinguish the sky from the obstacles. The GNSS satellites can be then classified as Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) by projecting them on the fisheye images. The experimentation results show that, in an open sky context, the mean percentage of the sky view for the receiver on the foot during the stance phase of a walking cycle is higher than that in the hand. This leads to, on average, a higher number of visible satellites for foot-mounted receivers and better satellite geometry. The trajectory of the foot-mounted device is generally more accurate with less uncertainty in all the evaluated environments (open sky, suburban, deep urban and urban canyon). This preliminary research leads to a counter-intuitive outcome since the foot-mounted GNSS device is globally able to provide better positioning than the hand-held device. Accordingly, the foot-mounted GNSS device could be further considered as a more reliable fusion source for hybridization positioning systems used for safety-critical or reliability-critical applications.
BibTeX:
@inproceedings{Zhu2023,
  author = {Ni Zhu and Athanase Bouronopoulos and Thomas Leduc and Myriam Servières and Valérie Renaudin},
  title = {Evaluation of the Human Body Mask Effects on GNSS Wearable Devices for Outdoor Pedestrian Navigation Using Fisheye Sky Views},
  booktitle = {2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)},
  publisher = {IEEE},
  year = {2023},
  pages = {10p.},
  url = {https://hal.science/hal-04110732v1},
  doi = {10.1109/plans53410.2023.10140056}
}
Fu H, Bonis T, Renaudin V and Zhu N (2023), "A Computer Vision Approach for Pedestrian Walking Direction Estimation with Wearable Inertial Sensors: PatternNet", In 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)., April, 2023. , pp. 9p. IEEE.
Abstract: In this paper, we propose an image-based neural network approach (PatternNet) for walking direction estimation with wearable inertial sensors. Gait event segmentation and projection are used to convert the inertial signals to image-like tabular samples, from which a Convolutional Neural Network (CNN) extracts geometrical features for walking direction inference.
To embrace the diversity of individual walking characteristics and different ways to carry the device, tailor-made models are constructed based on individual users’ gait characteristics and the device-carrying mode. Experimental assessments of the proposed method and a competing method (RoNIN) are carried out in real life situations and over 3 km total walking distance, covering indoor and outdoor environments, involving both sighted and visually impaired volunteers carrying the device in three different ways: texting, swinging and in a jacket pocket. PatternNet estimates the walking directions with a mean accuracy between 7 to 10 degrees for the three test persons and is 1.5 times better than RONIN estimates.
BibTeX:
@inproceedings{Fu2023,
  author = {Hanyuan Fu and Thomas Bonis and Valerie Renaudin and Ni Zhu},
  title = {A Computer Vision Approach for Pedestrian Walking Direction Estimation with Wearable Inertial Sensors: PatternNet},
  booktitle = {2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)},
  publisher = {IEEE},
  year = {2023},
  pages = {9p},
  url = {https://hal.science/hal-04152049},
  doi = {10.1109/plans53410.2023.10140028}
}
Fu H, Renaudin V, Kone Y and Zhu N (2023), "Analysis of the Recent AI for Pedestrian Navigation With Wearable Inertial Sensors", IEEE Journal of Indoor and Seamless Positioning and Navigation., April, 2023. , pp. 1-13.
Abstract: Wearable devices embedding inertial sensors enable autonomous, seamless, and low-cost pedestrian navigation. Appealing it is, the approach faces several challenges: measurement noises, different device-carrying modes, different user dynamics, and individual walking characteristics. Recent research applies Artificial Intelligence (AI) to improve inertial navigation's robustness and accuracy. Our analysis identifies 2 main categories of AI approaches depending on the inertial signals segmentation: either using human gait events (steps or strides) or fixed-length inertial data segments. A theoretical analysis of the fundamental assumptions is carried out for each category. Two state-of-the-art AI algorithms (SELDA, RoNIN), representative of each category, and a gait-driven non-AI method (SmartWalk) are evaluated in a 2,17 km long open access dataset, representative of the diversity of pedestrians' mobility surroundings (open-sky, indoors, forest, urban, parking lot). SELDA is an AI-based stride length estimation algorithm, RoNIN is an AI-based positioning method, and SmartWalk is a gait-driven non-AI positioning method. The experimental assessment shows the distinct features in each category and their limits with respect to the underlying hypotheses. On average, SELDA, RoNIN, and SmartWalk achieve 8 m, 22 m, and 17 m average positioning errors (RMSE) respectively, on six testing tracks recorded with two volunteers in various environments.
BibTeX:
@article{,
  author = {Hanyuan FU, Valérie RENAUDIN, Yacouba KONE, Ni ZHU},
  title = {Analysis of the Recent AI for Pedestrian Navigation With Wearable Inertial Sensors},
  journal = {IEEE Journal of Indoor and Seamless Positioning and Navigation},
  year = {2023},
  pages = {1-13},
  url = {https://ieeexplore-ieee-org/abstract/document/10108968},
  doi = {10.1109/JISPIN.2023.3270123}
}
Kaiser S, Baudet P, Zhu N and Renaudin V (2023), "Investigations on pedestrian long-term trajectory prediction based on AI and environmental maps" Monterey, California, April, 2023. ION.
Abstract: In recent years, a great research interest came up on the automatic protection of road users like pedestrians, bicyclists, or cars. One main problem of it is the position estimation of all road users in order to avoid upcoming collisions. Additionally to that, accurate positioning systems that are able to predict the intention or the future trajectory of the road user from previous paths received increasing attention. This allows for predicting collisions and for being able to send an alert or even braking the car, which is necessary for collision avoidance systems. Besides the prediction of a car’s path, the intention prediction of Vulnerable Road Users (VRU) is increasingly investigated in the literature, which is more difficult due to the fact that it can even be more random. The term VRU often refers to pedestrians, cyclists and motorcyclists. However, according to [1], it is important to differentiate between the multiple road users. Thus, in this work, only pedestrians will be considered but the models and scenarios could be adapted to other types of VRU. The objective of this paper is to predict pedestrians’ long-term trajectories using Artificial Intelligence (AI) and environmental map, which aims to provide timely alerts for VRU in dangerous situations.
BibTeX:
@conference{,
  author = {Susanna Kaiser, Pierre Baudet, Ni Zhu, Valerie Renaudin },
  title = {Investigations on pedestrian long-term trajectory prediction based on AI and environmental maps},
  publisher = {ION},
  year = {2023},
  url = {https://elib.dlr.de/191959/}
}
Al Abiad N, Houdry E, Khoury CE, Renaudin V and Robert T (2022), "Validation of SmartStep: a data-driven inertial-signal step detection method on elderly people" , pp. 2. ISPGR World Congress.
Abstract: In this study, we aim at using a smartphone to calculate relevant falling risk features from the norm of signals collected during a semi-supervised walking test. We test whether these features are able to differentiate elderly fallers from non-fallers. The objective is to check whether a smartphone and semi-supervised test can give insights on falling risk.
BibTeX:
@conference{,
  author = {Nahime Al Abiad, Enguerran Houdry, Carlos El Khoury, Valérie Renaudin, Thomas Robert},
  title = {Validation of SmartStep: a data-driven inertial-signal step detection method on elderly people},
  publisher = {ISPGR World Congress},
  year = {2022},
  pages = {2},
  url = {https://hal.science/hal-03888051v1}
}
Al Abiad N, Houdry E, Khoury CE, Renaudin V and Robert T (2022), "Semi-supervised monitoring of gait for fall risk estimation using smartphones" SB 2022.
Abstract: In this study, we aim at using a smartphone to calculate relevant falling risk features from the norm of signals collected during a semi-supervised walking test. We test whether these features are able to differentiate elderly fallers from non-fallers. The objective is to check whether a smartphone and semi-supervised test can give insights on falling risk.
BibTeX:
@conference{,
  author = {Nahime Al Abiad, Enguerran Houdry, Carlos El Khoury, Valérie Renaudin, Thomas Robert},
  title = {Semi-supervised monitoring of gait for fall risk estimation using smartphones},
  publisher = {SB 2022},
  year = {2022},
  url = {https://hal.science/hal-03862312v1}
}
Al Abiad N, Kone Y, Renaudin V and Robert T (2022), "Smartstep: a robust STEP detection method based on SMARTphone inertial signals driven by gait learning", IEEE Sensors Journal. Vol. 22(12), pp. 12288 - 12297. Institute of Electrical and Electronics Engineers (IEEE).
Abstract: Step detection is critical for many applications including health and indoor navigation. However, it remains challenging to achieve robust step detection for all types of human gait and sensors locations on the user’s body. The challenge increases for blind people whose gait is different from sighted and affected by the use of navigation aids. In this study, we propose and evaluate a new machine-learning-based step detection method: Smartstep. The advantages of this method are that it does not rely on any sensor-position, step-mode, and hand motion mode pre-classifications, nor on any threshold calibration. The method had already shown a promising performance with 99% recall and precision when applied in challenging conditions on young adults’ gait. In this study, the ability of this method to generalize to blind gait is put to question. The performance is assessed on two different blind people walking datasets including various challenging conditions (different walking speeds, smartphone placements, hand motion modes, sensor types, and navigation aids). Smartstep achieves a 99% precision or 1% overcount rate and a 90% recall or 10% undercount rate. This study demonstrates the robustness of the method and encourages its usage for other applications and populations.
BibTeX:
@article{Abiad2022,
  author = {Nahime Al Abiad and Yacouba Kone and Valerie Renaudin and Thomas Robert},
  editor = {IEEE},
  title = {Smartstep: a robust STEP detection method based on SMARTphone inertial signals driven by gait learning},
  journal = {IEEE Sensors Journal},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  year = {2022},
  volume = {22},
  number = {12},
  pages = {12288 - 12297},
  url = {https://ieeexplore.ieee.org/document/9761967},
  doi = {10.1109/jsen.2022.3169621}
}
Fu H, Kone Y, Renaudin V and Zhu N (2022), "A Survey on Artificial Intelligence for Pedestrian Navigation with Wearable Inertial Sensors", In IPIN2022., September, 2022.
Abstract: Miniaturized IMU (inertial measurement units) are widely integrated in wearable devices, promoting the versatile and low cost pedestrian inertial navigation technology, especially for indoor environment. In recent years, AI (Artificial Intelligence) is applied to improve the performance of this technology. AI methods work with data samples, thus it is important to select a suitable process for segmenting the inertial data sequences. This survey classifies AI methods for pedestrian inertial navigation into two categories, namely human gait driven methods and sampling frequency driven methods, according to their data segmentation process. Human gait driven methods segment the inertial measurement sequence by gait (step or stride) events and learn to infer a gait vector (step/stride length and direction) given a gait segment. Sampling frequency driven methods learn to infer the user’s velocity or change in position given a fixed length segment of inertial measurements. The survey studies the underlying assumptions and their validity of the two categories of AI methods. Two methods (SELDA and RoNIN), each from a category, are chosen for evaluation and comparison, on three testing tracks totaling 770m, covering indoor and outdoor environment, including stairs. The experiments highlight the two methods’ advantages and limitations, supporting the theoretical analyses. The selected methods achieve 7m and 12m positioning errors, respectively.
BibTeX:
@inproceedings{Fu2022,
  author = {Hanyuan Fu and Yacouba Kone and Valérie Renaudin and Ni Zhu},
  title = {A Survey on Artificial Intelligence for Pedestrian Navigation with Wearable Inertial Sensors},
  booktitle = {IPIN2022},
  year = {2022},
  url = {https://hal-univ-eiffel.archives-ouvertes.fr/hal-03781496}
}
Manzini N, Orcesi A, Thom C, Brossault M-A, Botton S, Ortiz M and Dumoulin J (2022), "Machine Learning Models Applied to a GNSS Sensor Network for Automated Bridge Anomaly Detection", Journal of Structural Engineering., September, 2022. Vol. 148(11) American Society of Civil Engineers (ASCE).
Abstract: Structural health monitoring (SHM) based on global navigation satellite systems (GNSS) is an interesting solution to provide absolute positions at different locations of a structure in a global reference frame. In particular, low-cost GNSS stations for large-scale bridge monitoring have gained increasing attention these last years because recent experiments showed the ability to achieve a subcentimeter accuracy for continuous monitoring with adequate combinations of antennas and receivers. Technical solutions now allow displacement monitoring of long bridges with a cost-effective deployment of GNSS sensing networks. In particular, the redundancy of observations within the GNSS network with various levels of correlations between the GNSS time series makes such monitoring solution a good candidate for anomaly detection based on machine learning models, using several predictive models for each sensor (based on environmental conditions, or other sensors as input data). This strategy is investigated in this paper based on GNSS time series, and an anomaly indicator is proposed to detect and locate anomalous structural behavior. The proposed concepts are applied to a cable-stayed bridge for illustration, and the comparison between multiple tools highlights recurrent neural networks (RNN) as an effective regression tool. Coupling this tool with the proposed anomaly detection strategy enables one to identify and localize both real and simulated anomalies in the considered data set.
BibTeX:
@article{Manzini2022,
  author = {Nicolas Manzini and André Orcesi and Christian Thom and Marc-Antoine Brossault and Serge Botton and Miguel Ortiz and John Dumoulin},
  title = {Machine Learning Models Applied to a GNSS Sensor Network for Automated Bridge Anomaly Detection},
  journal = {Journal of Structural Engineering},
  publisher = {American Society of Civil Engineers (ASCE)},
  year = {2022},
  volume = {148},
  number = {11},
  url = {https://hal-univ-eiffel.archives-ouvertes.fr/hal-03776743},
  doi = {10.1061/(asce)st.1943-541x.0003469}
}
Li Z, Zhu N and Renaudin V (2022), "Velocity Protection Level for Wearable Devices on TDCP-based Pedestrian Navigation", In 2022 International Conference on Localization and GNSS (ICL-GNSS)., June, 2022. IEEE.
Abstract: Wearable smart devices are now playing an important role in modern society. They can be used for locating the user thanks to embedded GNSS receivers and/or inertial sensors. A method based on GNSS carrier phase measurements, i.e. Time Difference Carrier Phase (TDCP), has shown a good performance in estimating user's velocity. However, in complex environments such as urban area where a large amount of multi-path reception could take place, the velocity estimated by TDCP could still be distorted. To inform the vulnerable users of the uncertainty on the velocity estimation for the safety-critical applications, a statistical velocity error bound, namely velocity Protection Level (PL), is calculated in this paper. In compliance with a pre-defined maximum velocity error tolerance called Alert Limit (AL), the velocity PL should be below or equal to the velocity AL. Otherwise, the user must be alerted in order to prevent him/her from dangerous accidents. In this research work, we proposed a horizontal velocity PL calculation method which is based on TDCP and Kalman filter, for the application of wearable positioning devices. A velocity AL is proposed for a specific scenario of blind people with white cane, since there is not any existing integrity specifications for pedestrian navigation. In urban environment, the velocity estimation mean error with proposed method is between 0.036 m/s and 0.053 m/s, and the Hazardously Misleading Information (HMI) rate can achieve the level of 10^-3, for a specific use case of blind people with a white cane.
BibTeX:
@inproceedings{Li2022,
  author = {Ziyou Li and Ni Zhu and Valerie Renaudin},
  title = {Velocity Protection Level for Wearable Devices on TDCP-based Pedestrian Navigation},
  booktitle = {2022 International Conference on Localization and GNSS (ICL-GNSS)},
  publisher = {IEEE},
  year = {2022},
  doi = {10.1109/icl-gnss54081.2022.9797022}
}
RENAUDIN V (2022), "Physics" vs "Brain": Challenge of labeling wearable inertial data for step detection for Artificial Intelligence", In IEEE Inertial 2022, 9th IEEE international symposium on inertial sensors and systems. Avignon, May, 2022. , pp. 4p. IEEE.
Abstract: Data-driven methods have attracted the research community from all sectors including positioning-based applications. However, the performances of the AI-based methods depend strongly on the quality of the data. With the fast development of powerful hardware, collecting, storing and training huge databases are not problematic anymore. The true bottleneck to AI is rather getting high-quality labeling of the data, especially for supervised learning. This paper aims at discussing the most suitable and efficient way to label the step instants of wearables, between the choices of using physical approaches and the pattern interpretation approach. Physical approaches refer to using highly accurate foot-mounted equipment to get the step instants then project them on the related body parts. While the pattern interpretation approach relies directly on the signal signatures interpreted with the help of human gait knowledge. It is referred to as the "brain" approach. Two machine learning-based step prediction models are trained with respectively the "physic" and "brain" labeling approach. The performance assessment shows that the step prediction model trained with brain labeling has a true positive detection rate around 85.9% - 95.7% with almost no overdetection while the model trained with physical labeling can only reach 54.7% of true positive rate with a high overdetection rate (around 36.7%).
BibTeX:
@inproceedings{RENAUDIN2022,
  author = {RENAUDIN, Valérie},
  title = {"Physics" vs "Brain": Challenge of labeling wearable inertial data for step detection for Artificial Intelligence},
  booktitle = {IEEE Inertial 2022, 9th IEEE international symposium on inertial sensors and systems},
  publisher = {IEEE},
  year = {2022},
  pages = {4p},
  url = {https://ieeexplore.ieee.org/abstract/document/9787763?casa_token=fhwX4sb5BKEAAAAA:S4p7dI0eUsEbTNXX9W3Quj2xy2zglRuTzxC7qAP8PLI_e1j3fF2quy8q5w1KClk30soUiFp5z-w},
  doi = {10.1109/inertial53425.2022.9787763}
}
RENAUDIN V (2022), "From Inertial Signals to Precise Pedestrian Indoor Positioning:Assessing Human Gait", In IEEE Inertial 2022, 9th IEEE international symposium on inertial sensors and systems. Avignon, May, 2022. , pp. 34p.
Abstract: From Inertial Signals to Precise Pedestrian Indoor Positioning:Assessing Human Gait (PowerPoint Presentation)
BibTeX:
@inproceedings{RENAUDIN2022a,
  author = {RENAUDIN, Valérie},
  title = {From Inertial Signals to Precise Pedestrian Indoor Positioning:Assessing Human Gait},
  booktitle = {IEEE Inertial 2022, 9th IEEE international symposium on inertial sensors and systems},
  year = {2022},
  pages = {34p},
  url = {https://hal.archives-ouvertes.fr/hal-03683848}
}
Al Abiad N, Kone Y, Renaudin V and Robert T (2021), "SMARTphone inertial sensors based STEP detection driven by human gait learning", In 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)., November, 2021. , pp. 8. IEEE.
Abstract: Robustly detecting steps with inertial sensors em- bedded in smartphones remains a challenging problem for pedestrian navigation, mainly due to the diversity of human gaits. In this paper, we propose a new step detection method for handheld devices, smartSTEP, that processes acceleration and gyroscope signals with machine learning techniques. The advantage of smartSTEP is that it does not rely on hand motion mode classifiers nor thresholds calibration. Trained on 9000 steps from 12 different participants and tested on approximately 2200 steps recorded on persons mostly not involved in the training, it achieved 99% recall and 98.9% precision in challenging scenarios such as asymmetrical walking, outdoor walking on different surfaces with different hand motion modes, and stairs climbing. A 0.097 seconds root mean square error is achieved on the predicted stride duration. This competes with the performances of present algorithms dedicated to calculating stride duration.
BibTeX:
@inproceedings{Abiad2021,
  author = {Al Abiad, Nahime and Yacouba Kone and Valerie Renaudin and Thomas Robert},
  title = {SMARTphone inertial sensors based STEP detection driven by human gait learning},
  booktitle = {2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {IEEE},
  year = {2021},
  pages = {8},
  url = {https://ieeexplore.ieee.org/abstract/document/9662513},
  doi = {10.1109/ipin51156.2021.9662513}
}
Kaiser S, Wei Y and Renaudin V (2021), "Analysis of IMU and GNSS Data Provided by Xiaomi 8 Smartphone", In 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)., November, 2021. , pp. 8. IEEE.
Abstract: The quality of positioning information given by smartphones is not always fully evident and might be inaccurate. With the possibility to access the Inertial Measurement Unit (IMU) data of the smartphone using the Android application program interface (API) functions and the Global Navigation Satellite System (GNSS) signals using the GNSS analysis App from Google, more or less unprocessed data is made available to developers and users. This enables the assessment of the quality of the smartphone chipsets and final positioning information. In this paper, we investigate the quality of available GNSS and IMU measurements and final track estimates of the smartphone. The analysis includes both static and dynamic measurements. A platform is developed to carry both, the smartphone and high accurate reference sensors for a fair comparison in the dynamic tests. The data of the different sensors are synchronized and the lever arm is removed. Open-sky and urban environments are considered for the GNSS analyses. Depending on the environment and on the dynamics, we show the different quality impairments of the data in this paper. Moreover, the Google Android indicators are investigated and their consistency and context with the data are provided.
BibTeX:
@inproceedings{Kaiser2021,
  author = {Susanna Kaiser and Yazheng Wei and Valerie Renaudin},
  title = {Analysis of IMU and GNSS Data Provided by Xiaomi 8 Smartphone},
  booktitle = {2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {IEEE},
  year = {2021},
  pages = {8},
  url = {https://ieeexplore.ieee.org/abstract/document/9662533},
  doi = {10.1109/ipin51156.2021.9662533}
}
Zhu N, Renaudin V, Ortiz M, Kone Y, Ichard C, Ricou S and Gueit F (2021), "Foot-mounted INS for Resilient Real-time Positioning of Soldiers in Non-collaborative Indoor Surroundings", In 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)., November, 2021. , pp. 8. IEEE.
Abstract: This paper presents a wearable positioning system which is able to provide real-time positioning information for all kinds of environments in a robust way. The system is mainly based on a foot-mounted INS assisted by a GNSS receiver as well as a barometer. The scenario presented in this paper took place during the final competition of the challenge MALIN (MAîtrise de la Localisation INdoor) organized by the DGA (Direction Générale de l’Armement) and the French National Research Agency (ANR). The objective of this challenge is to create a positioning system to track emergency response agents in non-collaborative environments, where GNSS signals are usually defeated. The proposed INS-based foot-mounted system is able to provide highly accurate positioning for various motion types (walking, running, stairs, ladder) thanks to a machine learning-based Zero Velocity Detector (ZVD). The external GNSS receiver is used to capture the GNSS positions in favorable conditions and further to provide absolute position and orientation corrections via a least square-based point pattern matching algorithm. The proposed system is tested over a 2.5 km trajectory in a soldier scenario including complex outdoor and deep indoor environments. The proposed system was able to provide real-time positioning information with an accuracy around 0.3% of error over the total traveled distance. The 75% HPE remains below 8 m and the 75% VPE is under 3 m.
BibTeX:
@inproceedings{Zhu2021,
  author = {Ni Zhu and Valerie Renaudin and Miguel Ortiz and Yacouba Kone and Cecile Ichard and Sander Ricou and Frederic Gueit},
  title = {Foot-mounted INS for Resilient Real-time Positioning of Soldiers in Non-collaborative Indoor Surroundings},
  booktitle = {2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {IEEE},
  year = {2021},
  pages = {8},
  url = {https://ieeexplore.ieee.org/abstract/document/9662561},
  doi = {10.1109/ipin51156.2021.9662561}
}
Konan F (2021), "Apprentissage et reconnaissance de balises virtuelles pour l'amélioration de la géolocalisation des déficients visuels". Thesis at: Université du Littoral Côte d'Opale., September, 2021. , pp. 43p.
Abstract: De nos jours, de nombreuses applications basées sur les smartphones aident au déplacement des personnes. Cependant, elles présentent des précisions insuffisantes [9] pour guider les déficients visuels et les itinéraires estimés souffrent de dérives et d'erreurs de positionnement dues au système GNSS et à la faible qualité des capteurs inertiels embarqués dans les smartphones. Aussi, il faut noter qu'il existe très peu d'applications qui ont été développées spécifiquement dans le sens de l'amélioration de la navigation des déficients visuels. C'est dans ce contexte que le Laboratoire commun Inmob (Labcom Inmob) a proposé ce sujet en vue de résoudre ces problèmes. Le Labcom Inmob est une collaboration entre le Laboratoire Géoloc de l'université Gustave Eiffel et l'entreprise Okeenea dont le but est de mutualiser leurs compétences pour satisfaire les enjeux et besoins des services de mobilité dédiées aux personnes en situation de handicap. Ainsi, pour répondre à des exigences de performances plus grandes, des technologies avec des balises, qui sont pour la plupart du temps physiques, sont commercialisées comme la solution Evelity de l'entreprise Okeenea. En effet, avec celles-ci la précision dépend fortement de la densité des balises. Il y a donc nécessité de déploiement dune infrastructure physique pour atteindre les objectifs escomptés en termes de performances. Par conséquent, des coûts de déploiement et surtout de maintenance sont générés, ce qui représente des dépenses supplémentaires par rapport à la solution sans balise pour les industries et entreprises qui fournissent ces solutions. Du coup, la question du coût et de la flexibilité de la solution se pose. Aussi, vu que la solution est dédiée à des déficients visuels, le caractère temps réel de la solution est plus que nécessaire pour éviter d'éventuels dégâts ou accidents. Problématiques et objectifs Le problème à résoudre se résume dans la question suivante : Comment guider en temps réel et de manière précise un déficient visuel sans déployer une infrastructure terrestre ? L'objectif à long terme est de développer une solution utilisable sur smartphone répondant aux défis de précision en terme de guidage des aveugles, soit une précision dans l'ordre du centimétrique. Cependant l'objectif spécifique assigné à ce stage est l'analyse des trajectoires des déficients visuels calculées à partir d'une solution de référence GNSS (Global Navigation Satellite System) et l'évaluation des performances.
BibTeX:
@report{KONAN2021,
  author = {Konan, Franck},
  title = {Apprentissage et reconnaissance de balises virtuelles pour l'amélioration de la géolocalisation des déficients visuels},
  school = {Université du Littoral Côte d'Opale},
  year = {2021},
  pages = {43p},
  url = {http://madis-externe.ifsttar.fr/exl-php/cadcgp.php?CMD=CHERCHE&MODELE=vues/ifsttar_internet_recherche_experte/tpl-r.html&WHERE_IS_DOC_REF_LIT=DOC00033671&&TABLE=ILS_DOC}
}
Wang N, Zhu N and Renaudin V (2021), "Construction of a Robust AI based Quasi static Magnetic Field Detector for Pedestrian Navigation". Thesis at: Ecole Centrale Nantes, 46p.
Abstract: There are 5 parts in total: Part1 is the introduction of the laboratory and internship; Part2 is the state of the art of the sensors,QSF detection algorithms and machine learning and deep learning methods that we used in this project; Part3 is Finding QSF features and introducing approaches of pre-processing data and construction of database; Part4 is description of the specific model construction; Part5 is the analysis of the results,the performances of different models and the comparison; Part6 is the conclusions and perspectives of this internship.
BibTeX:
@masterthesis{ILS_DOC:148821,
  author = {Wang, Ning and Zhu, Ni and Renaudin, Valérie},
  title = {Construction of a Robust AI based Quasi static Magnetic Field Detector for Pedestrian Navigation},
  school = {Ecole Centrale Nantes},
  year = {2021},
  pages = {46p}
}
Ragoin C and Renaudin V (2021), "La jungle des applications de mobilité sur smartphone : une enquête pour les classifier", In 3èmes Rencontres Francophones Transport Mobilité, 22p.
Abstract: De nos jours, il existe de nombreux sujets de recherches autour de la mobilité et de la transition numérique ayant besoin d'utiliser des applications sur smartphone. Le smartphone, doté d'une puce GNSS (Global Navigation Satellite System) et d'applications mobiles pouvant l'exploiter, peut par exemples servir d'outil principal à la réalisation d'enquêtes cherchant à étudier la mobilité de la population, que ça soit sur leur déplacements quotidiens ou leurs pratiques touristiques (Calvignac & Smolinski, 2017). Que l'on parle d'études sur la mobilité des voyageurs ou de recherches scientifiques en positionnement, nombreux sont les chercheurs à se demander quelle application ou quel logiciel utiliser. Il n'existe pas de méthodologie ou base de données permettant d'accompagner ce choix. Les études existantes se concentrent sur une zone géographique ou un usage unique comme le déplacement en transport en commun en Alsace (Dreyer, 2017). De plus, avec la révolution numérique de ces dernières années, le nombre d'applications mobiles autour de la mobilité ne cesse de croître. En janvier 2020, le Google Play Store, qui est une des banques d'applications pour les téléphones sous Android, contenait plus de 2.900.000 applications avec environ 45.000 nouvellement ajoutées au seul mois de janvier (AppTornado GmBH, 2020). 4,9% sont classées dans les catégories «Voyage et Local, Cartes et Navigation» (Clement, 2020), ce qui correspond à 122.500 applications sur ces thèmes, et ce, en 11 ans seulement d'existence du système d'exploitation Android. Il y a donc de quoi se perdre lors du choix d'une application. Une autre problématique souvent constatée est liée à la difficulté d'évaluer la qualité et l'intégrité des données recueillies par les applications mobiles (Desvignes & Jacquot, 2014). Si l'on prend pour exemple une trace GPS sur un fond de carte, fournie par une application mobile, il est souvent difficile d'estimer la précision réelle de celle-ci. En conséquence, les études des traces peuvent aboutir à une incompréhension sur les écarts relevés. Il est compliqué de tirer des conclusions sur des données que l'on ne maîtrise mal. Pour aider et faciliter le choix d'applications numériques, une enquête en ligne a été réalisée afin de recenser et de caractériser les applications et logiciels en lien avec la mobilité. Cette étude est au coeur de ce papier. Elle s'adressait au personnel de l'Université Gustave Eiffel et comprenait des questions sur les caractéristiques de chaque application. Le but de cette enquête est d'alimenter la construction d'une plateforme originale de recensement qualifié des applications et logiciels afin d'accompagner la recherche multicritères d'applications numériques sur la mobilité. Une innovation de cette plateforme est d'associer à chaque application un ou plusieurs correspondants disponibles et connaissant l'application pour répondre aux interrogations du futur utilisateur et ainsi bénéficier de leur expérience.
BibTeX:
@inproceedings{ILS_DOC:148025,
  author = {Ragoin, Céline and Renaudin, Valérie},
  title = {La jungle des applications de mobilité sur smartphone : une enquête pour les classifier},
  booktitle = {3èmes Rencontres Francophones Transport Mobilité},
  year = {2021},
  pages = {22p.},
  url = {https://hal.archives-ouvertes.fr/hal-03256931/}
}
Ortiz M, Zhu N, Renaudin V and Ramesh A (2021), "Datasets and Supporting Materials for the IPIN 2020 Competition Track 4 (Foot-Mounted IMU based Positioning, off-site)".
Abstract: This package contains the datasets and supplementary materials used in the IPIN 2020 Competition (Nantes , France).
Contents:
track4_ipin2020competition.pdf: Call for competition including the technical annex describing the competition
01-Logfiles: This folder contains 2 zip files.
- HKB08.zip : for sensors bias estimation.
- HKB43.zip : for trajectory estimation.
Each archive contains 4 files :
- HKBxx_mag.csv : magnetometer data
- HKBxx_sti.csv : inertial data
- HKBxx_ublox.ubx : GNSS data
- HKBxx_INFO.txt : info file
see track4_ipin2020competition.pdf for more details.
02-Supplementary_Materials: This folder contains the datasheet files of the different sensors.
03-Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on all evaluation points. The ground truth is provided csv file.
BibTeX:
@misc{Ortiz2021,
  author = {Ortiz, Miguel and Zhu, Ni and Renaudin, Valérie and Ramesh, Aravind},
  title = {Datasets and Supporting Materials for the IPIN 2020 Competition Track 4 (Foot-Mounted IMU based Positioning, off-site)},
  publisher = {Zenodo},
  year = {2021},
  url = {https://zenodo.org/record/4668618#.YG2mJs9xfIU},
  doi = {10.5281/ZENODO.4668618}
}
Servières M, Renaudin V, Dupuis A and Antigny N (2021), "Visual and Visual-Inertial SLAM: State of the Art, Classification, and Experimental Benchmarking", Journal of Sensors., February, 2021. Vol. 2021, pp. 1-26. Hindawi.
Abstract: Simultaneous Localization and Mapping is now widely adopted by many applications, and researchers have produced very dense literature on this topic. With the advent of smart devices, embedding cameras, inertial measurement units, visual SLAM (vSLAM), and visual-inertial SLAM (viSLAM) are enabling novel general public applications. In this context, this paper conducts a review of popular SLAM approaches with a focus on vSLAM/viSLAM, both at fundamental and experimental levels. It starts with a structured overview of existing vSLAM and viSLAM designs and continues with a new classification of a dozen main state-of-the-art methods. A chronological survey of viSLAM’s development highlights the historical milestones and presents more recent methods into a classification. Finally, the performance of vSLAM is experimentally assessed for the use case of pedestrian pose estimation with a handheld device in urban environments. The performance of five open-source methods Vins-Mono, ROVIO, ORB-SLAM2, DSO, and LSD-SLAM is compared using the EuRoC MAV dataset and a new visual-inertial dataset corresponding to urban pedestrian navigation. A detailed analysis of the computation results identifies the strengths and weaknesses for each method. Globally, ORB-SLAM2 appears to be the most promising algorithm to address the challenges of urban pedestrian navigation, tested with two datasets.
BibTeX:
@article{Servieres2021,
  author = {Servières, Myriam and Renaudin, Valérie and Dupuis, Alexis and Antigny, Nicolas},
  editor = {Stelios M. Potirakis},
  title = {Visual and Visual-Inertial SLAM: State of the Art, Classification, and Experimental Benchmarking},
  journal = {Journal of Sensors},
  publisher = {Hindawi},
  year = {2021},
  volume = {2021},
  pages = {1-26},
  doi = {10.1155/2021/2054828}
}
Koné Y, Zhu N and Renaudin V (2021), "Zero Velocity Detection without Motion Pre-classification: Uniform AI Model for All pedestrian Motions (UMAM)", IEEE Sensors Journal, 9p. Institute of Electrical and Electronics Engineers - IEEE.
Abstract: Foot-mounted positioning devices are becoming more and more popular in the different application field. For example, inertial sensors are now embedded in safety shoes to monitor security. They allow positioning with zero velocity update to bound the error growth of foot-mounted inertial sensors. High positioning accuracy depends on robust zero velocity detector (ZVD). Existing Artificial Intelligent (AI)-based methods classify the pedestrian dynamics to adjust ZVD at the cost of high computation costs and error propagation from miss-classification. We propose a machine learning model to detect zero velocity moments without any pre-classification step, named Uniform AI Model for All pedestrian Motions (UMAM). Performance is evaluated by benchmarking on two new subjects of opposite gender and different size, not included in the training data set, over complex indoor/outdoor paths of 2 km for subject 1 and 2.1 km for subject 2. We obtain an average 2D loop closure error of less than 0.37%.
BibTeX:
@article{ILS_DOC:148748,
  author = {KONE, Yacouba and ZHU, Ni and RENAUDIN, Valérie},
  title = {Zero Velocity Detection without Motion Pre-classification: Uniform AI Model for All pedestrian Motions (UMAM)},
  journal = {IEEE Sensors Journal},
  publisher = {Institute of Electrical and Electronics Engineers - IEEE},
  year = {2021},
  pages = {9p},
  url = {https://ieeexplore.ieee.org/abstract/document/9495821},
  doi = {10.1109/JSEN.2021.3099860}
}
Perul J and Renaudin V (2021), "BIKES: Bicycle Itinerancy Kalman filter with Embedded Sensors for challenging urban environment", IEEE Sensors Journal, 8p. Institute of Electrical and Electronics Engineers (IEEE).
Abstract: The use of bicycles is regaining popularity, especially in city centers where they can be used as quickly as cars and reduce carbon footprint. However, in these dense urban environments, navigation methods based on GNSS technologies do not provide sufficient accuracy for cyclist navigation and safety. To mitigate the challenges of indoor-like surroundings, a new positioning algorithm: BIKES (Bicycle Itinerancy Kalman filter with Embedded Sensors) was developed. This extended Kalman filter processes deeply degraded GNSS data to update velocity and position estimates with differential computation approaches working even in degraded environments. GNSS signals are combined with inertial and magnetic data to continuously estimate the trajectory when GNSS is unavailable. BIKES’ performance was tested in real-life conditions on a 3 km long path in the city center downtown Nantes and compared to Google Fused Location Provider estimates. A mean positioning error below 1 m with a 0.5 m standard deviation is achieved. These results are 4 times better than the Google solution. This algorithm allows also distinguishing if the cyclist is riding on a bike path, the sidewalk, or the road, which is critical for guidance systems
BibTeX:
@article{Perul2021,
  author = {Perul, Johan and Renaudin, Valérie},
  title = {BIKES: Bicycle Itinerancy Kalman filter with Embedded Sensors for challenging urban environment},
  journal = {IEEE Sensors Journal},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  year = {2021},
  pages = {8p},
  url = {https://ieeexplore.ieee.org/document/9446152/keywords#keywords},
  doi = {10.1109/jsen.2021.3086004}
}
Zhu N, Ortiz M, Renaudin V, Ichard C and Ricou S (2021), "Dataset of the intermediate competition in challenge MALIN: Indoor–outdoor inertial navigation system data for pedestrian and vehicle with high accuracy references in a context of firefighter scenario", Data in Brief., feb, 2021. Vol. 34, pp. 106626. Elsevier.
Abstract: This paper provides a multiple sensor dataset collected by the CyborgLOC team during the intermediate competition of the Challenge MALIN (MAîtrise de la localisation INdoor), which is a competition for indoor/outdoor real-time positioning. The sensors, including a GNSS receiver Ublox NEO-M8N, a Realsense D435i stereo camera, three Xsens MTi-300 and one PERSY (PEdestrian Reference SYstem), are mounted on different parts of the subject's body. The PERSY is a foot-mounted positioning device with a tri-axial accelerometer, a tri-axial gyroscope, a tri-axial magnetometer as well as a GNSS receiver Ublox M8T. The two scenarios are designed in a training centre of firefighters CFIS (Fire and Rescue Training Centre) in Blois, France to simulate the situation of firefighters during interventions. With total distances around 2?km for each scenario, the travelled trajectories passed through challenging environments including indoor, outdoor, urban canyon. The indoor part contains different stair levels, from the underground up to the 6th floor. The travel modes are vehicles and pedestrians. Several classical activities of firefighters are realized such as walking, running, stair-climbing, side-walking, crawling, passing above/below obstacles, carrying a stretcher, ladder climbing, etc. High accurate ground truth of stationary points and enclosing volumes are provided by the organizers of the competition, i.e., the Directorate General of Armaments (DGA: Direction Générale de l'Armement). Provided with raw data, they allow the evaluation of the positioning performances. This dataset is available on the data repository https://doi.org/10.5281/zenodo.4290789.
BibTeX:
@article{Zhu2021,
  author = {Zhu, Ni and Ortiz, Miguel and Renaudin, Valérie and Ichard, Cécile and Ricou, Sander},
  title = {Dataset of the intermediate competition in challenge MALIN: Indoor–outdoor inertial navigation system data for pedestrian and vehicle with high accuracy references in a context of firefighter scenario},
  journal = {Data in Brief},
  publisher = {Elsevier},
  year = {2021},
  volume = {34},
  pages = {106626},
  url = {https://www.sciencedirect.com/science/article/pii/S2352340920315067?via=ihub},
  doi = {10.1016/j.dib.2020.106626}
}
Renaudin V (2021), "Indoor positioning technologies: limitless creativity to model the complexity of cities and human gaits", Talk on ICE Seminar (Telecom Paris)., February, 2021.
Abstract: Over the past 15 years, there has been an exponential growth of new technologies for indoor positioning and navigation. Unlike GNSS technology, which has become the leading solution for outdoor positioning, no technology has taken the lead indoors. With the price drop of radio beacons, we see massive deployment of beacons’ networks for positioning. Image processing is progressing fast thanks to machine learning techniques that improve the rendering of very low-cost cameras. More and more smart devices embed inertial sensors providing autonomous navigation options. These are only a few of the technologies deployed. Hybridizing technologies to find the best compromise between accuracy, cost and energy consumption is at the heart of ongoing development. The nature of sensors in the infrastructure or smart devices, specific use cases requirements and privacy concerns about geolocated data are all features used to choose the right technologies to hybridize. Adopting a ubiquitous approach that combines dead reckoning and absolute positioning while recognizing the application and environmental context is certainly a strong trend in current developments and research. Given the great diversity of existing positioning systems and ways of presenting their performance, it seems almost impossible to provide a clear comparison of localization performance. The key to this comparison certainly lies in experimental comparative trials, in the same context and on identical scenarios. This approach started several years ago with international positioning competitions. This talk will review main indoor positioning technologies according to several comparison criteria. It will also exploit the results of the 2018 Indoor Positioning Indoor Navigation(IPIN) international competition that took place in a 9’000m² shopping mall (Atlantis) in Nantes (France) where 49 teams competed.
BibTeX:
@unpublished{Renaudin2021,
  author = {Renaudin, Valérie},
  title = {Indoor positioning technologies: limitless creativity to model the complexity of cities and human gaits},
  year = {2021},
  url = {https://www.telecom-paris.fr/agenda/ice-seminar-indoor-positioning-technologies-limitless-creativity-to-model-the-complexity-of-cities-and-human-gaits}
}
Al-Abiad N, Renaudin V and Robert T (2020), "Assessing gait variability from cellphone IMU placed in several locations: a feasibility study", Computer Methods in Biomechanics and Biomedical Engineering., October, 2020. Vol. 23(sup1), pp. S1-S3. Taylor & Francis.
Abstract: Cellphones have transformed how people live, work, and communicate. Similarly, they are becoming excessively popular in reshaping the healthcare system because of their accessibility, affordability, and capacity. Inside cellphones are integrated MEMS-designed Inertial Measurement Units (IMU). These MEMS provide a practical and cheap way to collect user’s motion data. They are mainly used in the area of sports (i.e., step count) and clinical applications (assessment of the user’s physical function, fall detection, etc.…). Moreover, gait analysis relying on inertial data acquired by cellphones has been a subject of many recent studies (Pepa et al. 2017; Roeing et al. 2017). Cellphones offer an easy and non-obtrusive way for ambulatory gait analysis.
A famous parameter known for its ability to reflect underlying neural control of gait, physiology of gait, and age-related and pathological alterations in locomotor regulations is gait variability (Hausdorff 2005). Several dedicated devices have been used to measure gait variability in clinical settings. However, the possibility of assessing gait variability with a cellphone in an uncontrolled and natural environment is hardly mentioned in the literature. Several intriguing research questions arise when trying to treat this matter. Most importantly is what algorithm can be used to calculate gait variability from cellphone IMU data, and how much can the cellphone algorithm-position influence gait variability interpretation.
The objective of this feasibility study is to assess the feasibility and limitations of using a simple approach (peak detection algorithms) to detect steps and segment the walking motion into gait cycles or strides and thus compute gait variability as the standard deviation of stride time.
BibTeX:
@article{Abiad2020,
  author = {Al-Abiad, Nahime and Renaudin, Valérie and Robert, Thomas },
  title = {Assessing gait variability from cellphone IMU placed in several locations: a feasibility study},
  journal = {Computer Methods in Biomechanics and Biomedical Engineering},
  publisher = {Taylor & Francis},
  year = {2020},
  volume = {23},
  number = {sup1},
  pages = {S1-S3},
  url = {https://www.tandfonline.com/doi/full/10.1080/10255842.2020.1811490},
  doi = {10.1080/10255842.2020.1811490}
}
Manzini N, Orcesi A, Thom C, Brossault M-A, Botton S, Ortiz M and Dumoulin J (2020), "Performance analysis of low-cost GNSS stations for structural health monitoring of civil engineering structures", Structure and Infrastructure Engineering., 11, 2020. , pp. 1-17. Taylor and Francis.
Abstract: Global Navigation Satellite Systems (GNSS) have been used in various monitoring applications for the past two decades, as one of the very few options to provide absolute positions in a global reference frame. However, high performance GNSS stations are expensive, and sometimes may be impractical because of their size, power consumption or software requirements. Thus, the use of low-cost GNSS stations for structural health monitoring (SHM) has gained increasing attention. This paper presents a detailed experimental assessment of multiple combinations of GNSS receivers and antennas, and highlights an optimal cost-efficient solution for monitoring applications. Several sets of processing parameters and constraints are also evaluated using open source RTKLib software. The performance of the proposed solution is evaluated through two experimental dynamic scenarios, proving its ability to track quick displacements down to 4 mm and oscillations of 1 cm with a frequency up to 0.25 Hz with a 1 Hz receiver. Finally, a two-week dataset acquired from on a network of low-cost GNSS stations deployed on a suspended bridge is used to validate on-site performance. Results show good agreement between GNSS time series, traditional displacement sensors, and numerical simulations made using an operational mechanical model of the bridge, highlighting the potential of such low-cost solutions for structural health monitoring applications.
BibTeX:
@article{Manzini2020,
  author = {Nicolas Manzini and André Orcesi and Christian Thom and Marc-Antoine Brossault and Serge Botton and Miguel Ortiz and John Dumoulin},
  title = {Performance analysis of low-cost GNSS stations for structural health monitoring of civil engineering structures},
  journal = {Structure and Infrastructure Engineering},
  publisher = {Taylor and Francis},
  year = {2020},
  pages = {1-17},
  url = {https://www.tandfonline.com/doi/full/10.1080/15732479.2020.1849320},
  doi = {10.1080/15732479.2020.1849320}
}
Potorti F, Park S, Crivello A, Palumbo F, Girolami M, Barsocchi P, Lee S, Torres-Sospedra J, Jimenez AR, Perez-Navarro A, Mendoza-Silva GM, Seco F, Ortiz M, Perul J, Renaudin V, Kang H, Park S, Lee JH, Park CG, Ha J, Han J, Park C, Kim K, Lee Y, Gye S, Lee K, Kim E, Choi J, Choi Y-S, Talwar S, Cho SY, Ben-Moshe B, Scherbakov A, Antsfeld L, Sansano-Sansano E, Chidlovskii B, Kronenwett N, Prophet S, Landau Y, Marbel R, Zheng L, Peng A, Lin Z, Wu B, Ma C, Poslad S, Selviah DR, Wu W, Ma Z, Zhang W, Wei D, Yuan H, Jiang J-B, Huang S-Y, Liu J-W, Su K-W, Leu J-S, Nishiguchi K, Bousselham W, Uchiyama H, Thomas D, Shimada A, Taniguchi R-I, Cortes V, Lungenstrass T, Ashraf I, Lee C, Ali MU, Im Y, Kim G, Eom J, Hur S, Park Y, Opiela M, Moreira A, Nicolau MJ, Pendao C, Silva I, Meneses F, Costa A, Trogh J, Plets D, Chien Y-R, Chang T-Y, Fang S-H and Tsao Y (2020), "The IPIN 2019 Indoor Localisation Competition - Description and Results", IEEE Access., November, 2020. Vol. 8, pp. 206674-206718. Institute of Electrical and Electronics Engineers (IEEE).
Abstract: IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000m2 outdoors and and 6000m2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks.
BibTeX:
@article{Potorti2020,
  author = {Francesco Potorti and Sangjoon Park and Antonino Crivello and Filippo Palumbo and Michele Girolami and Paolo Barsocchi and Soyeon Lee and Joaquin Torres-Sospedra and Antonio Ramon Jimenez and Antoni Perez-Navarro and German M. Mendoza-Silva and Fernando Seco and Miguel Ortiz and Johan Perul and Valerie Renaudin and Hyunwoong Kang and Soyoung Park and Jae Hong Lee and Chan Gook Park and Jisu Ha and Jaeseung Han and Changjun Park and Keunhye Kim and Yonghyun Lee and Seunghun Gye and Keumryeol Lee and Eunjee Kim and Jeongsik Choi and Yang-Seok Choi and Shilpa Talwar and Seong Yun Cho and Boaz Ben-Moshe and Alex Scherbakov and Leonid Antsfeld and Emilio Sansano-Sansano and Boris Chidlovskii and Nikolai Kronenwett and Silvia Prophet and Yael Landau and Revital Marbel and Lingxiang Zheng and Ao Peng and Zhichao Lin and Bang Wu and Chengqi Ma and Stefan Poslad and David R. Selviah and Wei Wu and Zixiang Ma and Wenchao Zhang and Dongyan Wei and Hong Yuan and Jun-Bang Jiang and Shao-Yung Huang and Jing-Wen Liu and Kuan-Wu Su and Jenq-Shiou Leu and Kazuki Nishiguchi and Walid Bousselham and Hideaki Uchiyama and Diego Thomas and Atsushi Shimada and Rin-Ichiro Taniguchi and Vicente Cortes and Tomas Lungenstrass and Imran Ashraf and Chanseok Lee and Muhammad Usman Ali and Yeongjun Im and Gunzung Kim and Jeongsook Eom and Soojung Hur and Yongwan Park and Miroslav Opiela and Adriano Moreira and Maria Joao Nicolau and Cristiano Pendao and Ivo Silva and Filipe Meneses and Antonio Costa and Jens Trogh and David Plets and Ying-Ren Chien and Tzu-Yu Chang and Shih-Hau Fang and Yu Tsao},
  title = {The IPIN 2019 Indoor Localisation Competition - Description and Results},
  journal = {IEEE Access},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  year = {2020},
  volume = {8},
  pages = {206674-206718},
  url = {https://ieeexplore.ieee.org/document/9253514},
  doi = {10.1109/access.2020.3037221}
}
Perul J and Renaudin V (2020), "HEAD: smootH Estimation of wAlking Direction with a handheld device embedding inertial, GNSS, and magnetometer sensors", NAVIGATION., September, 2020. , pp. 14p.
Abstract: Abstract Pedestrian navigation with handheld sensors is still particularly complex. Pedestrian Dead Reckoning method is generally used, but the estimation of the walking direction remains problematic because the device's pointing direction does not always correspond to the walking direction. To overcome this difficulty, it is possible to use gait modeling based approaches. But, these methods suffer from sporadic erroneous estimates and their accumulation over time. The HEAD (smootH Estimation of wAlking Direction) filter uses WAISS and MAGYQ angular estimates as observations to correct the walking direction and to obtain more robust and smooth results. TDCP updates are applied to constrain the walking direction estimation error while pseudo-ranges directly update the position. HEAD is tested by 5 subjects over 21 indoor/outdoor acquisitions (between 720 m and 1.3 km). A 54% improvement is achieved thanks to the fusion in texting mode. The median obtained angular error is 5.5 in texting mode and 12 in pocket mode.
BibTeX:
@article{Perul,
  author = {Perul, Johan and Renaudin, Valérie},
  title = {HEAD: smootH Estimation of wAlking Direction with a handheld device embedding inertial, GNSS, and magnetometer sensors},
  journal = {NAVIGATION},
  year = {2020},
  pages = {14p},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/navi.389},
  doi = {10.1002/navi.389}
}
Ponte Müller F, Munoz Diaz E, Perul J and Renaudin V (2020), "Urban Vulnerable Road User Localization using GNSS, Inertial Sensors and Ultra-Wideband Ranging", In 2020 IEEE Intelligent Vehicles Symposium. 20-23/10/2020, Las Vegas, USA., October, 2020. , pp. 7p. IEEE.
Abstract: Over the last decade, the number of accidents involving Vulnerable Road Users (VRU), i.e. pedestrians, cyclists and motorbike drivers, has not decreased in the same way as accidents between passenger cars have. Cooperative systems based on Vehicle-to-X (V2X) communication make it possible to directly exchange information between VRUs and vehicles and to increase the overall situational awareness beyond the capabilities of on-board ranging sensors. To detect and avoid collisions, vehicles require up-to-date and precise information on the location and trajectory of VRUs. In this paper, we propose a VRU localization system based on Global Navigation Satellite System (GNSS), inertial sensors and ultra-wideband (UWB) round-trip-delay ranging technology. We present an exhaustive measurement campaign comprising pedestrians, cyclists and vehicles performed in an urban setting and show first results on the localization performance for a pedestrian crossing an intersection. In the experiments, the pedestrian inertial system supported by GNSS and UWB ranges is able to achieve 0.65m 1-position accuracy.
BibTeX:
@inproceedings{PonteMueller2020,
  author = {Ponte Müller, Fabian and Munoz Diaz, Estefania and Perul, Johan and Renaudin, Valérie.},
  title = {Urban Vulnerable Road User Localization using GNSS, Inertial Sensors and Ultra-Wideband Ranging},
  booktitle = {2020 IEEE Intelligent Vehicles Symposium. 20-23/10/2020, Las Vegas, USA},
  publisher = {IEEE},
  year = {2020},
  pages = {7p},
  url = {https://ieeexplore.ieee.org/abstract/document/9304671},
  doi = {10.1109/IV47402.2020.9304671}
}
Ruotsalainen L, Renaudin V, Pei L, Piras M, Marais J, Cavalheri E and Kaasalainen S (2020), "Toward autonomous driving in arctic areas", IEEE Intelligent Transportation Systems Magazine., June, 2020. Vol. 12, pp. 10-24. IEEE.
Abstract: This article provides an overview of the use of inertial and visual sensors and discusses their prospects in the Arctic navigation of autonomous vehicles. We also examine the fusion algorithms used thus far for integrating vehicle localization measurements as well as the map-matching (MM) algorithms relating position coordinates with road infrastructure. Our review reveals that conventional fusion and MM methods are not enough for navigation in challenging environments, like urban areas and Arctic environments. We also offer new results from testing inertial and optical sensors in vehicle positioning in snowy conditions. We find that the fusion of Global Navigation Satellite System (GNSS) and inertial navigation systems (INSs) does not provide the accuracy required for automated driving, and the use of optical sensors is challenged by snow covering the road markings. Although extensive further research is needed to solve these problems, the fusion of GNSS, INSs, and optical sensors seems to be the best option due to their complementary nature.
BibTeX:
@article{Ruotsalainen2020,
  author = {Ruotsalainen, Laura and Renaudin, Valerie and Pei, Ling and Piras, Marco and Marais, Juliette and Cavalheri, Emerson and Kaasalainen, Sanna},
  title = {Toward autonomous driving in arctic areas},
  journal = {IEEE Intelligent Transportation Systems Magazine},
  publisher = {IEEE},
  year = {2020},
  volume = {12},
  pages = {10-24},
  url = {https://ieeexplore.ieee.org/document/9115644},
  doi = {10.1109/MITS.2020.2994014}
}
Ragoin C, Renaudin V and Ortiz M (2020), "Precise positioning on smartphones: which implementation strategy to adopt?", In 4th GNSS Raw Measurements Taskforce Workshop., June, 2020. , pp. 12p. European GNSS Supervisory Authority (GSA).
Abstract: The aim of the GSA’s Raw Measurements Task Force is to bridge the knowledge gap between raw measurement users. The GNSS Raw Measurements Task Force Workshops are a key element in this effort, providing a forum for stakeholders to share experience and knowledge around raw measurements use.
BibTeX:
@inproceedings{Ragoin2020,
  author = {Ragoin, Celine and Renaudin, Valerie and Ortiz, Miguel},
  title = {Precise positioning on smartphones: which implementation strategy to adopt?},
  booktitle = {4th GNSS Raw Measurements Taskforce Workshop},
  publisher = {European GNSS Supervisory Authority (GSA)},
  year = {2020},
  pages = {12p},
  url = {https://hal.archives-ouvertes.fr/hal-02768847}
}
Kone Y, Zhu N, Renaudin V and Ortiz M (2020), "Machine Learning-Based Zero-Velocity Detection for Inertial Pedestrian Navigation", IEEE Sensors Journal., June, 2020. Vol. 20, pp. 11p. Institute of Electrical and Electronics Engineers - IEEE.
Abstract: Zero velocity update is a common and efficient approach to bound the accumulated error growth for foot-mounted inertial navigation system. Thus a robust zero velocity detector (ZVD) for all kinds of locomotion is needed for high accuracy pedestrian navigation systems. In this paper, we investigate two machine learning-based ZVDs: Histogram-based Gradient Boosting (HGB) and Random Forest (RF), aiming at adapting to different motion types while reducing the computation costs compared to the deep learning-based detectors. A complete data preprocessing procedure, including a feature engineering study and data augmentation techniques, is proposed. A motion classifier based on HGB is used to distinguish ”single support” and ”double float” motions. This concept is different from the traditional locomotion classification (walking, running, stair climbing) since it merges similar motions into the same class. The proposed ZVDs are evaluated with inertial data collected by two subjects over a 1.8 km indoor/outdoor path with different motions and speeds. The results show that without huge training dataset, these two machine learning-based ZVDs achieve better performances (55 cm positioning accuracy) and lower computational costs than the two deep learning-based Long Short-Term Memory methods (1.21 m positioning accuracy).
BibTeX:
@article{Kone2020,
  author = {Kone, Yacouba and Zhu, Ni and Renaudin, Valérie and Ortiz, Miguel},
  title = {Machine Learning-Based Zero-Velocity Detection for Inertial Pedestrian Navigation},
  journal = {IEEE Sensors Journal},
  publisher = {Institute of Electrical and Electronics Engineers - IEEE},
  year = {2020},
  volume = {20},
  pages = {11p},
  url = {https://ieeexplore.ieee.org/document/9107252},
  doi = {10.1109/JSEN.2020.2999863}
}
Dulery C, Ortiz M and Leblan X (2020), "EN 16803/ Référentiel Européen de géolocalisation pour certifier les solutions de mobilité", In 47ème Congrès ATEC ITS France., January, 2020. , pp. 9p.
Abstract: Le domaine de la géolocalisation s'est doté d'une méthodologie de référence indispensable pour évaluer et caractériser des terminaux GNSS destinés à la navigation terrestre. La série de normes EN16803 a pour objectif d'éclairer les choix des utilisateurs et de simplifier l'intégration des technologies satellitaires aux systèmes embarqués. Elle s'appuie sur une technique de métrologie instrumentale, identifiée sous le terme « Record & Replay » et offrant plusieurs avantages-clefs : - Restituer des environnements d'essais « Reproductibles » et « Représentatifs » du monde réel ; - Dissocier les erreurs de « Justesse » et de « Fidélité » pour enrichir les analyses ; - Etablir des scénarios de référence fiables pour « comparer les résultats de mesures ».
BibTeX:
@inproceedings{Dulery2020,
  author = {Dulery, Christelle and Ortiz, Miguel and Leblan, Xavier},
  title = {EN 16803/ Référentiel Européen de géolocalisation pour certifier les solutions de mobilité},
  booktitle = {47ème Congrès ATEC ITS France},
  year = {2020},
  pages = {9p},
  url = {https://guide-gnss.com/wp-content/uploads/2020/01/ATEC-ITS-Metrologie-GNSS-Referentiel-Europeen-de-geolocalisation-pour-certifier-les-solutions-de-Mobilite.pdf}
}
Renaudin V, Ortiz M and Ragoin C (2020), "Positionnement GNSS précis sur smartphone : une réalité proche ?", In Groupe de Travail GNSS et Positionnement de la CNIG., June, 2020. , pp. 13p.
Abstract: Groupe de Travail GNSS & Positionnement du CNIG (conseil national de l'information géographique).
BibTeX:
@inproceedings{Renaudin2020,
  author = {Renaudin, Valérie and Ortiz, Miguel and Ragoin, Céline},
  title = {Positionnement GNSS précis sur smartphone : une réalité proche ?},
  booktitle = {Groupe de Travail GNSS et Positionnement de la CNIG},
  year = {2020},
  pages = {13p},
  url = {https://cnig.gouv.fr/gt-gnss-positionnement-a12592.html}
}
(2020), "CEN standards in GNSS for Road/Automotive. Benefits of using EN16803 series for the automotive sector", December, 2020. European Committee for Standardization (CEN).
Abstract: Autonomous driving is among the most demanding road applications. It requires high accuracy coupled to a high level of integrity. Furthermore, the environment in which it operates is much harsher than its counterparts in other domains like aviation or maritime... This combination of requirements puts autonomous guidance systems in a situation where its assessment, certification and type-approval are very complex. New methodologies are clearly needed to be able to tackle the upcoming PPP (Precise Point Positioning) or NRTK (Network Real Time Kinematic) techniques.
The WG1 'Navigation and positioning receivers for road applications' of CEN/CLC JTC5 ‘Space’, whose Secretariat is currently held by BNAE (AFNOR), has been developing a standardization framework for assessing GNSS-based positioning systems. This framework relies on the EN16803 series on the use of GNSS-based positioning for ITS and on-going projects led by the WG1.
Since September 2020, the first version of the EN16803 series is available. The first three parts describe a methodology to assess GNSS devices based on Record & Replay (also known as Record and Playback). Part-1 is dedicated to ‘Definitions and system engineering procedures for the establishment and assessment of performances’, Part-2 to ‘Assessment of basic performances of GNSS-based positioning terminals’, and finally Part-3 to ‘Assessment of security performances of GNSS-based positioning terminals’. Part-2 and Part-3, JTC5-WG1 aims to propose operational methods to test in laboratory GNSS-based positioning systems. Considering Part-3 focuses on jamming and spoofing issues, while it is strictly forbidden to use jammers or spoofers in real life, alternative simulation techniques coupled to playback are proposed.
Miguel Ortiz, Convenor of JTC5-WG1 and EN 16803 series Project leader , commented: “Today, we are proud to see GNSS/GPS Geolocation Testing Laboratory like the GUIDE laboratory are already using the EN16803 series to assess GNSS receivers and to issue test reports only a couple of months after the publication of Part-2 & Part-3.”
In practical terms, laboratories wishing to evaluate the performances of a GNSS device can use EN16803, for instance, to assess "cross-track" accuracy (one metric among others). To do that, they have to replay a GNSS scenarios. Through one playback, producing one blue cross-track error in the example below (bottom left), it is possible determine the overall performance by averaging CDF (red trace, bottom right below). This CDF is specified in EN16803 to extract the key values (50-75-95 percentiles) used to classify the performance of the GNSS receiver. For instance, it is possible to visualise the result for 50 replays of a ublox F9P
In addition to the recent publication of EN16803 Parts 1, 2 and 3, JTC5-WG1 has been busy with the GPSTART2 project. This EC-funded project tackles positioning issues for autonomous driving applications (High Accuracy Service, and Integrity), and aims at complementing the current EN series with a new part dedicated to design of assessment scenarios. In order to achieve this challenging target, a European consortium bringing together GUIDE laboratory (FR), Technische Universität Braunschweig (DE), Radiolabs (IT), M3 Systems (BE) has been chosen. Four work packages have been defined and will lead to the publications of technical reports and technical specification related to:
• ‘Record & Replay scenario’: design and validation methodologies,
• ‘PVT error model’, or how to evaluate ‘End To End’ ITS application (Key Performance Indicators),
• ‘Integrity management on road applications’, from its definition to the way to verify it,
• ‘Assessment of hybridized GNSS device’ in laboratory in a certification framework.
The project will end in 2021.
To conclude, the EN16803 series aim at providing new methodologies enabling fair and affordable metrological comparisons between GNSS-based positioning systems. This can be achieved by replaying validated scenarios that contain real GNSS signals (and potentially additional sensors) recorded with a great accuracy. Moreover, EN16803 is designed to comply with the new type approval scheme needed for autonomous driving applications, which are very demanding in term of accuracy and integrity.
BibTeX:
@mvreference{StandardizationCEN2020,,
  editor = {European Committee for Standardization (CEN)},
  title = {CEN standards in GNSS for Road/Automotive. Benefits of using EN16803 series for the automotive sector},
  publisher = {European Committee for Standardization (CEN)},
  year = {2020},
  edition = {European Committee for Standardization (CEN)},
  url = {https://standards.cen.eu/dyn/www/f?p=204:7:0::::FSP_ORG_ID:1180941&cs=1B074935E38E22D9760DE5477DAC6E7AB}
}
Zhu N, Ortiz M and Renaudin V (2019), "Seamless Indoor-Outdoor Infrastructure-free Navigation for Pedestrians and Vehicles with GNSS-aided Foot-mounted IMU", In 2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN)., December, 2019. , pp. 8p. Institute of Electrical and Electronics Engineers - IEEE.
Abstract: With the highly development of navigation techniques during the past decades, the demand for seamless indoor-outdoor navigation is growing from different application fields especially for the military or the first response emergency services. For military applications, one of the key performance requirements is the availability of the positioning solutions for all kinds of dynamics in different environments. Furthermore, due to the stealth requirement in some military actions, it is impossible for military vehicles or personnel to emit signals which enable to be detected by their opponents. This limitation prevents the use of infrastructure-based cooperative localization techniques. The research work of this paper aims at facing the following challenging issues: firstly, to design a positioning filter which is adaptive to the dynamic changes between walking and driving; secondly, to find an approach that correctly identifies the transition between outdoor and indoor with reduced latency; finally, to construct a loosely coupling GNSS/IMU scheme which takes into account the GNSS signal distortion in indoor and urban spaces.Under this context, we propose a complete indoor-outdoor infrastructure-free positioning prototype including a foot-mounted reference navigation system named Pedestrian Reference System (PERSY) and a Ublox High Sensitivity GNSS (HS-GNSS) receiver (M8P). A loosely-coupled architecture between GNSS receiver and the PERSY is employed by using an indicator of horizontal position accuracy PACCH provided by the GNSS Ublox M8P receiver. This indicator allows qualifying the position solutions delivered by the GNSS receiver as well as detecting the transition of indoor/outdoor, which helps the PERSY to update with absolute positions from GNSS. This positioning prototype can take advantage of both GNSS and PERSY so as to realize a seamless indoor-outdoor positioning for pedestrians and vehicles. The proposed system is evaluated in two scenarios over respective...
BibTeX:
@inproceedings{Zhu2019,
  author = {Zhu, Ni and Ortiz, Miguel and Renaudin, Valerie},
  title = {Seamless Indoor-Outdoor Infrastructure-free Navigation for Pedestrians and Vehicles with GNSS-aided Foot-mounted IMU},
  booktitle = {2019 International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {Institute of Electrical and Electronics Engineers - IEEE},
  year = {2019},
  pages = {8p},
  url = {https://ieeexplore.ieee.org/abstract/document/8911741/},
  doi = {10.1109/IPIN.2019.8911741}
}
Renaudin V, Ortiz M, Perul J and al. (2019), "Evaluating Indoor Positioning Systems in a Shopping Mall: The Lessons Learned From the IPIN 2018 Competition", IEEE ACCESS., September, 2019. , pp. 148594-148628. Institute of Electrical and Electronics Engineers - IEEE.
Abstract: The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75 th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future.
BibTeX:
@article{Renaudin2019b,
  author = {Renaudin, Valerie and Ortiz, Miguel and Perul, Johan and al.},
  title = {Evaluating Indoor Positioning Systems in a Shopping Mall: The Lessons Learned From the IPIN 2018 Competition},
  journal = {IEEE ACCESS},
  publisher = {Institute of Electrical and Electronics Engineers - IEEE},
  year = {2019},
  pages = {148594-148628},
  url = {https://ieeexplore.ieee.org/document/8852722},
  doi = {10.1109/ACCESS.2019.2944389}
}
Renaudin V and Ortiz M (2019), "Véhicules autonomes", In 59e congrès annuel du club EEA., June, 2019.
Abstract: Présentation d'actions IFSTTAR sur le déploiement des véhicules autonomes, aspects industrialisation, recherche et enseignement.
BibTeX:
@inproceedings{Renaudin2019,
  author = {Renaudin, Valérie and Ortiz, Miguel},
  title = {Véhicules autonomes},
  booktitle = {59e congrès annuel du club EEA},
  year = {2019},
  url = {https://hal.archives-ouvertes.fr/hal-02158551}
}
Renaudin V (2019), "Indoor positioning: towards an infinite number of technologies?", In 10th Chinese Satellite Navigation Conference., May, 2019. , pp. 20p.
Abstract: Over the past 15 years, there has been an exponential growth of new technologies for indoor positioning and navigation. Unlike GNSS technology, which has become the leading solution for outdoor positioning, no technology has taken the lead indoors. With the price drop of radio beacons, we see a massive deployment of beacons' networks for positioning. Image processing is progressing fast thanks to machine learning techniques that improve the rendering of very low-cost cameras. More and more smart devices embed inertial sensors providing autonomous navigation options. These are only a few of the technologies deployed. Hybridizing technologies to find the best compromise between accuracy, cost and energy consumption is at the heart of ongoing development. The nature of sensors in the infrastructure or in smart devices, specific use cases requirements and privacy concerns about geolocated data are all features used to choose the right technologies to hybridize. Adopting a ubiquitous approach that combines dead reckoning and absolute positioning while recognizing the application and environmental context is certainly a strong trend in current developments and research. Given the great diversity of existing positioning systems and ways of presenting their performance, it seems almost impossible to provide a clear comparison of localization performance. The key to this comparison certainly lies in experimental comparative trials, in the same context and on identical scenarios. This approach started several years ago with international positioning competitions. This talk will review main indoor positioning technologies according to several comparison criteria. It will also exploit the results of last Indoor Positioning Indoor Navigation (IPIN) international competition that took place in a 9'000 m² shopping mall (Atlantis) in Nantes (France) where 49 teams competed.
BibTeX:
@inproceedings{Renaudin2019a,
  author = {Renaudin, Valérie},
  title = {Indoor positioning: towards an infinite number of technologies?},
  booktitle = {10th Chinese Satellite Navigation Conference},
  year = {2019},
  pages = {20p},
  url = {https://hal.archives-ouvertes.fr/hal-02142982}
}
Perul J and Renaudin V (2019), "Fusion of Attitude and Statistical Walking Direction Estimations with Time-Difference Carrier Phase Velocity Update for Pedestrian Dead Reckoning Method", In 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019)., September, 2019. , pp. 367-377. WILEY.
Abstract: Pedestrian location in urban or indoor environments is particularly complex. Indeed, GNSS technology generally used for localization is no longer sufficient in these challenging environments. However, the presence of many sensors in consumer equipment like smartphones allows the implementation of different methods. PDR (Pedestrian Dead Reckoning) is a position estimation method using inertial and magnetic sensor data. It is based on the determination of two elements: the step length and the walking direction. This direction is difficult to estimate for handheld sensors because the orientation of the sensor is not always aligned with the walking direction. Methods based on the study of horizontal hand accelerations can overcome this difficulty, but performance on real scenarios is not sufficient. This article proposes a new method for estimating the walking direction and position based on an extended Kalman filter. For this purpose, the angular estimates from the WAISS and MAGYQ algorithms are merged to update the estimate of the walking direction. Phase measurements are used with TDCP updates to correct the velocity and correct the walking direction. 6 experiments carried out with three subjects over distances between 650 and 1300m in texting mode, in real and challenging conditions are conducted. The mean angular error obtained is 4.6° and the mean position error is 0.5% of the travelled distance.
BibTeX:
@inproceedings{Perul2019,
  author = {Perul, Johan and Renaudin, Valérie},
  editor = {Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019)},
  title = {Fusion of Attitude and Statistical Walking Direction Estimations with Time-Difference Carrier Phase Velocity Update for Pedestrian Dead Reckoning Method},
  booktitle = {32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019)},
  publisher = {WILEY},
  year = {2019},
  pages = {367-377},
  url = {https://www.ion.org/publications/abstract.cfm?articleID=17035},
  doi = {10.33012/2019.17035}
}
Perul J and Renaudin V (2019), "Learning individual models to estimate the walking direction of mobile phone users", IEEE Sensors Journal., September, 2019. Vol. 19(24), pp. 10p. IEEE.
Abstract: Pedestrian Dead Reckoning algorithms are commonly used to assist pedestrian navigation with handheld sensors. The estimation of the walking direction remains an important source of positioning error of mobile phone users since this direction may be different from the device's pointing direction. A better understanding of human walking gait has enabled to produce new algorithms to mitigate the impact of the way the device is held in hand. WAISS algorithm is one of them. It is based on the study of horizontal hand accelerations and their modeling using Gaussian Mixture Models (GMM). However, ongoing search for universal modeling of handheld device carrying mode defeats the varying nature of human gait. This paper investigates the impact of individual gait characteristics and their modeling to improve the estimation of the walking direction. Different models are learned for curved and straight lines and varying GMM are proposed to account for inter-individual gait variations. This results in a reduced walking direction error with a 8.1° mean error to the 90th percentile computed for 3 subjects over a 1.5 km indoor/outdoor walk.
BibTeX:
@article{Perul2019a,
  author = {Perul, Johan and Renaudin, Valérie},
  title = {Learning individual models to estimate the walking direction of mobile phone users},
  journal = {IEEE Sensors Journal},
  publisher = {IEEE},
  year = {2019},
  volume = {19},
  number = {24},
  pages = {10p},
  url = {https://ieeexplore.ieee.org/document/8827533},
  doi = {10.1109/JSEN.2019.2940138}
}
Coiret A, Vandanjon PO, Deljanin E, Ortiz M and Lorino T (2019), "Management of road speed sectioning to lower vehicle energy consumption", In TIS Roma 2019, AIIT 2nd International Congress on Transport Infrastructure and Systems in a changing world., September, 2019. , pp. 8p. Elsevier.
Abstract: Efforts to limit climate change should concern the transportation sector which is responsible for roughly a quarter of greenhouse gas emissions. Aside from vehicle’s technical progress and driver eco-driving awareness, road infrastructure has a role to play in this environmental aim. At the project stage, the design of roads can avoid energy losses linked to marked ramps, but afterwards, during the use phase, road management can be a lever too.
In this use phase framework, our paper is focused on energy saving that can be achieved by managing speed sectioning. The key point is to ensure consistency between vehicle dynamics, road longitudinal profile and speed policy. Indeed, eco-driving could be impeded if a limiting speed sign is encountered on a steep slope or in a sharp turn. In such a situation the speed sign will be qualified as misplaced. Mechanical braking has then to be used instead of simple natural deceleration. In 2018 the French government lowered authorized speed on secondary roads, from 90 to 80 km/h, with road safety as the primary motivation. In order to assess energy impact of speed-sectioning for these two speed limits, experiments have been carried out in four experimental sites. Furthermore criterion and dissipated energy computation have been developed. The developed energy computation yields to determine the expected fuel economy for the entire traffic over a day on a selected route or network.
As a result, over consumption for a misplaced speed sign can reach up to 40 liters of fuel per day with an approaching speed of 80 km/h and 50 liters of fuel per day with an approaching speed of 90 km/h according to traffic data. Significant energy savings could therefore be achieved by sign placement optimization.
BibTeX:
@inproceedings{Coiret2019,
  author = {Coiret, Alex and Vandanjon, Pierre Olivier and Deljanin, Emir and Ortiz, Miguel and Lorino, Tristan},
  title = {Management of road speed sectioning to lower vehicle energy consumption},
  booktitle = {TIS Roma 2019, AIIT 2nd International Congress on Transport Infrastructure and Systems in a changing world},
  publisher = {Elsevier},
  year = {2019},
  pages = {8p},
  url = {https://www.sciencedirect.com/science/article/pii/S2352146520301551},
  doi = {10.1016/j.trpro.2020.02.105}
}
Ortiz M, Perul J, Torres-Sospedra J and Renaudin V (2019), "Datasets and Supporting Materials for the IPIN 2018 Competition Track 4 (Foot-Mounted IMU based Positioning, off-site)", May, 2019.
Abstract: This package contains the datasets and supplementary materials used in the IPIN 2018 Competition (Nantes, France).
BibTeX:
@dataset{Ortiz2019,
  author = {Ortiz, Miguel and Perul, Johan and Torres-Sospedra, Joaquin and Renaudin, Valérie},
  title = {Datasets and Supporting Materials for the IPIN 2018 Competition Track 4 (Foot-Mounted IMU based Positioning, off-site)},
  year = {2019},
  url = {https://zenodo.org/record/3228012},
  doi = {10.5281/ZENODO.3228012}
}
Grenier A and Renaudin V (2019), "Efficient Use of SSR RTCM Streams For Real-Time Precise Point Positioning on Smartphones", In 2019 16th Workshop on Positioning, Navigation and Communications (WPNC). Bremen, Germany, October, 2019. , pp. 6p. IEEE.
Abstract: Since the availability of GNSS raw measurements with Google Nougat API in 2016, research has been assessing smartphone performances and GNSS data's quality. The objective is to achieve precise positioning and to assess its quality. With the growing Internet of Things (IoT), embedded sensors spread everywhere for acquiring, assessing and monitoring the environment, for which low-cost and precise positioning is essential. Low-cost does not only relate to the financial cost of the GNSS receiver but also to other costs like data consumption, battery consumption and computation cost. Using the Google API and the new generation of smartphones, these costs can be targeted to produce smarter, more efficient, and optimized positioning solutions for being implemented on other IoT devices. This paper presents research on Real-Time Precise Point Positioning (PPP-RTK) application development in Android. Analysis of needed RTCM (Radio Technical Commission for Maritimes Services) streams is given along with the assessment of their benefits for efficient positioning. Focus is made on evaluating the cost of precise products in terms of internet data consumption.
BibTeX:
@inproceedings{Grenier2019a,
  author = {Grenier, Antoine and Renaudin, Valerie},
  title = {Efficient Use of SSR RTCM Streams For Real-Time Precise Point Positioning on Smartphones},
  booktitle = {2019 16th Workshop on Positioning, Navigation and Communications (WPNC)},
  publisher = {IEEE},
  year = {2019},
  pages = {6p},
  url = {https://ieeexplore.ieee.org/abstract/document/8970179},
  doi = {10.1109/WPNC47567.2019.8970179}
}
Antigny N, Uchiyama H, Servières M, Renaudin V, Thomas D and Taniguchi R-i (2019), "Solving Monocular Visual Odometry Scale Factor with Adaptive Step Length Estimates for Pedestrians Using Handheld Devices", sensors., February, 2019. Vol. 19(953), pp. 18p.
Abstract: The urban environments represent challenging areas for handheld device pose estimation (i.e., 3D position and 3D orientation) in large displacements. It is even more challenging with low-cost sensors and computational resources that are available in pedestrian mobile devices (i.e., monocular camera and Inertial Measurement Unit). To address these challenges, we propose a continuous pose estimation based on monocular Visual Odometry. To solve the scale ambiguity and suppress the scale drift, an adaptive pedestrian step lengths estimation is used for the displacements on the horizontal plane. To complete the estimation, a handheld equipment height model, with respect to the Digital Terrain Model contained in Geographical Information Systems, is used for the displacement on the vertical axis. In addition, an accurate pose estimation based on the recognition of known objects is punctually used to correct the pose estimate and reset the monocular Visual Odometry. To validate the benefit of our framework, experimental data have been collected on a 0.7 km pedestrian path in an urban environment for various people. Thus, the proposed solution allows to achieve a positioning error of 1.6–7.5% of the walked distance, and confirms the benefit of the use of an adaptive step length compared to the use of a fixed-step length.
BibTeX:
@article{Antigny2019,
  author = {Antigny, Nicolas and Uchiyama, Hideaki and Servières, Myriam and Renaudin, Valérie and Thomas, Diego and Taniguchi, Rin-Ichiro},
  title = {Solving Monocular Visual Odometry Scale Factor with Adaptive Step Length Estimates for Pedestrians Using Handheld Devices},
  journal = {sensors},
  year = {2019},
  volume = {19},
  number = {953},
  pages = {18p},
  url = {https://www.mdpi.com/1424-8220/19/4/953},
  doi = {10.3390/s19040953}
}
Renaudin V (2018), "Préparation de la compétition internationale de localisation intérieure IPIN : cartographie de parcours piétons", In Forum de l'Association Française de Topographie.
Abstract: Depuis quelques années des compétitions internationales destinées à comparer les technologies de localisation à l'intérieur des bâtiments sont organisées. Face à la diversification de ces technologies, elles permettent de fixer une cadre unique d'évaluation des performances de localisation en temps réel ou différé. Un levé topographique d'envergure qui combine mesures au théodolite, par GNSS différentiel et scanner 3D a permis de cartographier à 10 cm près les 180 cibles réparties dans le centre commercial Atlantis à Nantes. Ces cibles définissent les parcours sur lesquels les compétiteurs du congrès international IPIN s'affronteront le 22 septembre. Ce projet a été réalisé par quatre étudiants de l'ESGT sous la direction du laboratoire GEOLOC de l'IFSTTAR et avec le soutien de la société Viametris.
BibTeX:
@inproceedings{Renaudin2018c,
  author = {Renaudin, Valérie},
  title = {Préparation de la compétition internationale de localisation intérieure IPIN : cartographie de parcours piétons},
  booktitle = {Forum de l'Association Française de Topographie},
  year = {2018},
  url = {https://hal.archives-ouvertes.fr/hal-01896630/}
}
Renaudin V (2018), "Integrating human dimension in the development of pedestrian navigation", In ITSNT 2018, International Technical Symposium on Navigation and Timing. , pp. 34p.
Abstract: L'apparition de nouveaux objets connectés, portés au poignet, sur des bijoux ou des lunettes, offre de nouvelles opportunités d'améliorer la mobilité des personnes. Parallèlement, la complexité des mouvements humains pose de nouveaux défis dans le développement d'algorithmes de positionnement et de navigation. Trouver la bonne stratégie pour fusionner les signaux disponibles afin d'estimer les coordonnées de façon précise et fiable partout peut être complexe. Cet exposé présente l'état actuel et les tendances en navigation piétonnière, avec un accent sur les approches de navigation à l'estime. Il traite de l'intégration des caractéristiques de la démarche humaine afin d'améliorer les modèles d'estimation du déplacement. Une nouvelle utilisation des données numériques urbaines et des mesures de signaux radio urbains dégradés pour améliorer l'estimation de l'emplacement des piétons dans le filtre d'hybridation est également présentée.
BibTeX:
@inproceedings{Renaudin2018d,
  author = {Renaudin, Valérie},
  title = {Integrating human dimension in the development of pedestrian navigation},
  booktitle = {ITSNT 2018, International Technical Symposium on Navigation and Timing},
  year = {2018},
  pages = {34p},
  url = {https://www.itsnt.fr/proceedings-and-past-editions/}
}
Antigny N, Servières M and Renaudin V (2018), "Fusion of 3D GIS, Vision, Inertial and Magnetic Data for Improved Urban Pedestrian Navigation and Augmented Reality Applications", Navigation, Journal of the Institute of Navigation., September, 2018. Vol. 65, pp. 431-447.
Abstract: In the context of pedestrian navigation and Augmented Reality applications in urban environments, we propose to fuse the pose estimated through a vision process, thanks to a precisely known 3D model, with inertial and magnetic measurements. First, this allows for updating a Pedestrian Dead‐Reckoning process and improving the positioning accuracy. Second, a trusted pose estimate allows us to reproject 3D Geographical Information System content in Augmented Reality with qualified confidence. Because 3D Geographical Information System data are provided by many sources inducing an inhomogeneous precision and level of quality, being able to qualify these 3D contents is important to validate their relevance to use them. A long pedestrian path of 3 km in an urban environment with a sparsely known 3D model of urban furniture was conducted. This has permitted validation of the contribution of sensor fusion that improves the positioning accuracy and allows characterization of the 3D Geographical Information System content directly on‐site using Augmented Reality. Performance is presented in terms of positioning accuracy in urban spaces.
BibTeX:
@article{Antigny2018a,
  author = {Antigny, Nicolas and Servières, Myriam and Renaudin, Valérie},
  title = {Fusion of 3D GIS, Vision, Inertial and Magnetic Data for Improved Urban Pedestrian Navigation and Augmented Reality Applications},
  journal = {Navigation, Journal of the Institute of Navigation},
  year = {2018},
  volume = {65},
  pages = {431-447},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/navi.254},
  doi = {10.1002/navi.254}
}
Renaudin V, Moreau N, Billey A, Lamblin A, Vos J, Perul J and Ortiz M (2018), "Préparation de la compétition internationale de localisation intérieure IPIN : cartographie de parcours piétons", XYZ., October, 2018. Vol. 155, pp. 17-21.
Abstract: Depuis quelques années des compétitions internationales destinées à comparer les technologies de localisation à l’intérieur des bâtiments sont organisées. Face à la diversification de ces technologies, elles permettent de fixer une cadre unique d’évaluation des performances de localisation en temps réel ou différé. Un levé topographique d’envergure qui combine mesures au théodolite, par GNSS différentiel et scanner 3D a permis de cartographier à 10 cm près les 180 cibles réparties dans le centre commercial Atlantis à Nantes. Ces cibles définissent les parcours sur lesquels les compétiteurs du congrès international IPIN ’affronteront le 22 septembre. Ce projet a été réalisé par quatre étudiants de l’ESGT sous la direction du laboratoire GEOLOC de l’IFSTTAR et avec le soutien de la société Viametris.
BibTeX:
@article{Renaudin2018,
  author = {Renaudin, Valérie and Moreau, Nicolas and Billey, Antoine and Lamblin, Alexandre and Vos, Jasper and Perul, Johan and Ortiz, Miguel},
  title = {Préparation de la compétition internationale de localisation intérieure IPIN : cartographie de parcours piétons},
  journal = {XYZ},
  year = {2018},
  volume = {155},
  pages = {17-21},
  url = {https://www.aftopo.org/download.php?type=pdf&matricule=aHR0cHM6Ly93d3cuYWZ0b3BvLm9yZy93cC1jb250ZW50L3VwbG9hZHMvYXJ0aWNsZXMvcGRmL2FydGljbGU0MTU1MDUucGRm}
}
Renaudin V (2018), "ULISS and PERSY: Research Equipment for the positioning and navigation of travelers"
Abstract: ULISS is an innovative hardware developed at GEOLOC laboratory for upper body part mounted based personal navigation research. Raw tri-axis inertial, barometric and magnetic signals at 200 Hz and raw GNSS measurements at 5Hz. PERSY is a foot mounted hardware & software developed at GEOLOC laboratory. Raw tri-axis inertial and magnetic signals at 160 Hz and raw GNSS measurements at 5Hz.
BibTeX:
@article{Renaudin2018a,
  author = {Renaudin, Valerie},
  title = {ULISS and PERSY: Research Equipment for the positioning and navigation of travelers},
  year = {2018},
  url = {https://geoloc.univ-gustave-eiffel.fr/fileadmin/redaction/GEOLOC/Equipements/plaquette_equipement/UlissPersy-plaquette-fr.pdf}
}
Renaudin V (2018), "Human dimensions of navigation", In The Israel Navigation Workshop and Exhibition INWE18. Hertzliya, Israel (January)
Abstract: Itzhack Bar Itzhack invited plenary lecture at the The Israel Navigation Workshop and Exhibition INWE18
BibTeX:
@inproceedings{Renaudin2018b,
  author = {Renaudin, Valerie},
  title = {Human dimensions of navigation},
  booktitle = {The Israel Navigation Workshop and Exhibition INWE18},
  year = {2018},
  number = {January},
  url = {https://hal.archives-ouvertes.fr/hal-01901990/}
}
Perul J and Renaudin V (2018), "Building individual inertial signals models to estimate PDR walking direction with smartphone sensors", In International Conference on Indoor Positioning and Indoor Navigation. Nantes, France, September, 2018. , pp. 24-27.
Abstract: Inertial and magnetic sensors based PDR approaches are particularly interesting for pedestrian location since they don't require any specific infrastructure. Estimating the walking direction, which is essential for PDR strategy, remains difficult with handheld sensors. WAISS is a new method that integrates hand movement and is independent of the misalignment between the walking direction and the pointing direction that estimates the walking direction. It uses statistical models of the hand accelerations in the horizontal plane. The paper studies how to create the best possible models. Among the features under study are the number of strides used to learn the models, different acquisition contexts and walking directions. Finally, the complexity of models needed for a given person is discussed. 100 strides over curved and straight line walks combined with a bi-modal Gaussian Mixture Model gives the best walking direction estimate with a 15° mean error over a 325 m indoor/outdoor walk performed by four subjects.
BibTeX:
@inproceedings{Perul2018,
  author = {Perul, Johan and Renaudin, Valerie},
  title = {Building individual inertial signals models to estimate PDR walking direction with smartphone sensors},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation},
  year = {2018},
  pages = {24-27},
  url = {https://ieeexplore.ieee.org/abstract/document/8533722/},
  doi = {10.1109/IPIN.2018.8533722}
}
Antigny N, Servières M and Renaudin V (2018), "Continuous Pose Estimation for Urban Pedestrian Applications on Hand-held Mobile Device", In International Conference on Indoor Positioning and Indoor Navigation. Nantes, France (September), pp. 8p.
Abstract: To support pedestrian navigation in urban and indoor spaces, an accurate pose estimate (i.e. 3D position and 3D orientation) of an equipment held in hand constitutes an essential point in the development of mobility assistance tools (e.g. Augmented Reality applications). On the assumption that the pedestrian is only equipped with general public devices, the pose estimation is restricted to the use of low-cost sensors embedded in the latter (i.e. an Inertial and Magnetic Measurement Unit and a monocular camera). In addition, urban and indoor spaces, comprising closely-spaced buildings and ferromagnetic elements, constitute challenging areas for sensor pose estimation during large pedestrian displacements. However, the recent development and provision of 3D Geographical Information System content by cities constitutes a wealth of data usable for pose estimation. To address these challenges, we propose an autonomous sensor fusion framework for pedestrian hand-held device pose estimation in urban and indoor spaces. The proposed solution integrates inertial and magnetic-based attitude estimation, monocular Visual Odometry with pedestrian motion estimation for scale estimation and known 3D geospatial object recognition based absolute pose estimation. Firstly, this allows to continuously estimate a qualified pose of the device held in hand. Secondly, an absolute pose estimate enables to update and to improve the positioning accuracy. To assess the proposed solution, experimental data has been collected, for four different people, on a 0.5 km pedestrian walk in an urban space with sparse known objects and indoors passages. According to the performance evaluation, the sensors fusion process enhanced the pedestrian localization in areas where conventional hand-held systems were not accurate or available.
BibTeX:
@inproceedings{Antigny2018,
  author = {Antigny, Nicolas and Servières, Myriam and Renaudin, Valérie},
  editor = {IEEE},
  title = {Continuous Pose Estimation for Urban Pedestrian Applications on Hand-held Mobile Device},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation},
  year = {2018},
  number = {September},
  pages = {8p},
  url = {https://hal.archives-ouvertes.fr/hal-02018726/}
}
Abid M, Renaudin V, Robert T, Aoustin Y and Le Carpentier E (2018), "A Simulation-based Approach to Generate Walking Gait Accelerations for Pedestrian Navigation Solutions", In International Conference on Indoor Positioning and Indoor Navigation. Nantes, France , pp. 9p.
Abstract: In indoor environments, pedestrian dead reckoning (PDR) is the most used strategy for pedestrian position estimation from inertial data collected with handheld devices. PDR process recursively estimates positions using step length estimation based on parametric models that take into consideration some physiological parameters, displacement features and acceleration statistical properties. The coefficients of these models need frequent adjustment to limit cumulative errors induced by alteration of gait pattern. A large experimental database providing information about human locomotion variability is required for this calibration. However, the development of such database is costly in terms of time and effort. To make the collected data as reliable as possible, several gait-affecting factors should be considered, which highly increases the number of measurement trials. In this paper, we propose an alternative way of generating locomotion data that consists in simulating human walking gait motion under different conditions. We propose a multibody system simulator taking into account possible step-level asymmetry induced by handling a device in hand, as well as the correlation between arms and legs motions during gait. Our simulation approach was evaluated with data from overground walking experiments on one test subject. Preliminary results show some similarities between acceleration profiles related to different body parts, and the same variation trends of selected acceleration items in function of carrying mode and gait velocity.
BibTeX:
@inproceedings{Abid2018,
  author = {Abid, Mahdi and Renaudin, Valérie and Robert, Thomas and Aoustin, Yannick and Le Carpentier, Eric},
  title = {A Simulation-based Approach to Generate Walking Gait Accelerations for Pedestrian Navigation Solutions},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation},
  year = {2018},
  pages = {9p},
  url = {https://hal.archives-ouvertes.fr/hal-01997361/},
  doi = {10.1109/IPIN.2018.8533858}
}
ManziniI N, Orcesi A, Thom C, Botton S, Clement A, Ortiz M and Dumoulin J (2018), "Use of low-cost GNSS receivers for Structural Health Monitoring", In 40th IABSE Symposium : Tomorrow's Megastructures. Nantes, France, September, 2018. , pp. 8p. International Association for Bridge and Structural Engineering - IABSE.
Abstract: Global Positioning System (GPS) is a satellite constellation allowing positioning in a constantly updated global reference frame for almost any user on the globe. Over the last decade, GPS has been expanded to Global Navigation Satellite Systems (GNSS) with the progressive addition of three satellite constellations. This evolution enables a more robust and effective positioning calculation, thus improving the performance and reliability of GNSS-based monitoring systems. In parallel, improvements in GNSS receivers provide higher frequency and precision calculations, with shorter computation time, enabling GNSS techniques to be used both for long-term monitoring of slow displacements, and for the analysis of short term events. This paper explores the performances and possibilities of low-cost GNSS receivers in order to improve structural health monitoring systems of large and flexible structures such as bridges, towers or cooling-towers. Low-cost carrier-phase receivers, coupled with various processing methods and parameters, are evaluated to the extent of characterizing both long term precision and stability, and qualification of short displacements and oscillations. The amplitudes and frequencies of displacements and oscillations tested are selected in accordance with phenomena that may be observed on flexible structures. The use of a high-quality reference station with very short baseline is proven a good alternative over expensive receiver upgrading, with rovers able to qualify abrupt displacements down to 4mm, and accurately monitor oscillations with frequencies up to 0.25Hz and amplitudes down to 1cm with a 1Hz sampling rate. Data acquired from a low-cost receiver installed on the main span of suspended bridge is evaluated in order to highlight quality and reliability of on-site applications, and was found highly correlated to traditional sensors data (resistance temperature detectors, and displacement laser sensors).
BibTeX:
@inproceedings{Manzini2018a,
  author = {Manzini, Nicolas and Orcesi, André and Thom, Christian and Botton, Serge and Clement, Antoine and Ortiz, Miguel and Dumoulin, John},
  title = {Use of low-cost GNSS receivers for Structural Health Monitoring},
  booktitle = {40th IABSE Symposium : Tomorrow's Megastructures},
  publisher = {International Association for Bridge and Structural Engineering - IABSE},
  year = {2018},
  pages = {8p},
  note = {40th IABSE Symposium : Tomorrow's Megastructures, NANTES, FRANCE, 19-/09/2018 - 21/09/2018},
  url = {https://hal.archives-ouvertes.fr/hal-01914930}
}
Manzini N, Orcesi A, Thom C, Clement A, Botton S, Ortiz M and Dumoulin J (2018), "Structural Health Monitoring using a GPS sensor network", In 9th European Workshop on Structural Health Monitoring Series (EWSHM). Manchester, UK, July, 2018. , pp. 12p. British Institute of Non Destructive Testing.
Abstract: Over the last decade, the rapid expansion of Global Navigation Satellite Systems (GNSS) coupled with the incremental improvements on the existing GPS constellation has continuously increased the robustness of satellite positioning, therefore significantly improving the reliability and the possibilities of a GNSS-based structural health monitoring system. Moreover, thanks to constant evolution, GPS-only receivers have proven to be more and more efficient with relatively simple hardware, provided that they are used in an appropriate workflow such as relative positioning with short baselines. This paper presents an application of a network of cost-effective GPS receivers as a part of a monitoring system. Monitoring data are acquired from a network of a dozen of GPS 'Geocube' stations installed on a suspended bridge, the Brotonne Bridge, in France. One main objective of this network is to be able to detect some changes in bridge behaviour. Data from GPS sensor is analysed and correlated with traditional data, such as piers temperature. This study validates that a GPS sensor network can provide useful and reliable data for structural monitoring.
BibTeX:
@inproceedings{Manzini2018,
  author = {Manzini, Nicolas and Orcesi, Andre and Thom, Christian and Clement, Antoine and Botton, Serge and Ortiz, Miguel and Dumoulin, John},
  title = {Structural Health Monitoring using a GPS sensor network},
  booktitle = {9th European Workshop on Structural Health Monitoring Series (EWSHM)},
  publisher = {British Institute of Non Destructive Testing},
  year = {2018},
  pages = {12p},
  note = {9th European Workshop on Structural Health Monitoring Series (EWSHM), MANCHESTER, ROYAUME-UNI, 10-/07/2018 - 13/07/2018},
  url = {https://hal.archives-ouvertes.fr/hal-01915943}
}
Combettes C and Renaudin V (2017), "Walking direction estimation based on statistical modeling of human gait features with handheld MIMU", IEEE/ASME Transactions on Mechatronics., December, 2017. Vol. 22(6), pp. 2502-2511.
Abstract: Contrary to Global Navigation Satellite System or Wi-Fi based navigation, pedestrian dead reckoning (PDR) method with handheld inertial and magnetic sensors gives the opportunity to achieve indoor/outdoor ubiquitous pedestrian localization. A remaining PDR critical issue is the estimation of the walking direction. Existing methods are principally searching for the energy main axis, but they do not consider the variability of hand movements introducing robustness issues. A new method, based on statistical models and likelihood maximization adjusted to the person and his/her activity, is proposed in this paper. Performance is assessed with experiments in a motion capture room and a shopping mall. The new statistical approach gives globally better results than state of the art methods. A 1.4° to 15.3° error on the walking direction estimates is found over several “1-km walk” tests indoors.
BibTeX:
@article{Combettes2017,
  author = {Combettes, Christophe and Renaudin, Valerie},
  title = {Walking direction estimation based on statistical modeling of human gait features with handheld MIMU},
  journal = {IEEE/ASME Transactions on Mechatronics},
  year = {2017},
  volume = {22},
  number = {6},
  pages = {2502-2511},
  url = {http://ieeexplore.ieee.org/document/8078215/},
  doi = {10.1109/TMECH.2017.2765005}
}
Abid M, Renaudin V, Aoustin Y, Le-Carpentier E and Robert T (2017), "Walking Gait Step Length Asymmetry Induced by Handheld Device", IEEE Transactions on Neural Systems and Rehabilitation Engineering., November, 2017. Vol. 25(11), pp. 2075-2083.
Abstract: The modeling and feature extraction of human gait motion are crucial in biomechanics studies, human localization and robotics applications. Recent studies in pedestrian navigation aim at extracting gait features based on the data of low-cost sensors embedded in handheld devices such as smartphones. The general assumption in Pedestrian Dead Reckoning (PDR) strategy for navigation application is that the presence of a device in hand does not impact the gait symmetry and that all steps are identical. This hypothesis, which is used to estimate the traveled distance, is investigated in this paper with an experimental study. Ten healthy volunteers participated in motion lab tests with a 0.190 kg device in hand. Several walking trials with different device carrying modes and several gait speeds were performed. For a fixed walking speed, it is shown that the steps differ in their duration when holding a mass equivalent to a smartphone mass, which invalidates classical symmetry hypothesis in PDR step length modeling. It is also shown that this hypothesis can lead to a 2.5 to 6.3% error on the PDR estimated traveled distance for the different walking trials.
BibTeX:
@article{Abid2017,
  author = {Abid, Mahdi and Renaudin, Valerie and Aoustin, Yannick and Le-Carpentier, Eric and Robert, Thomas},
  title = {Walking Gait Step Length Asymmetry Induced by Handheld Device},
  journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
  year = {2017},
  volume = {25},
  number = {11},
  pages = {2075-2083},
  url = {http://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=medp&NEWS=N&AN=28541210 https://ieeexplore.ieee.org/document/7931687/},
  doi = {10.1109/TNSRE.2017.2705285}
}
Antigny N, Servieres M and Renaudin V (2017), "[POSTER] An Inertial, Magnetic and Vision Based Trusted Pose Estimation for AR and 3D Data Qualification on Long Urban Pedestrian Displacements", In IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct)., October, 2017. , pp. 168-169. IEEE.
Abstract: In the context of pedestrian navigation, urban environment constitutes a challenging area for both localization and Augmented Reality (AR). In order to display 3D Geographic Information System (GIS) content in AR and to qualify them, we propose to fuse the pose estimated using vision thanks to a precisely known 3D urban furniture model with rotation estimated from inertial and magnetic measurements. An acquisition conducted in urban environment on a long pedestrian path permits to validate the contribution of sensors fusion and allows to qualify the pose estimation needed for AR 3D GIS content characterization.
BibTeX:
@inproceedings{Antigny2017a,
  author = {Antigny, Nicolas and Servieres, Myriam and Renaudin, Valerie},
  title = {[POSTER] An Inertial, Magnetic and Vision Based Trusted Pose Estimation for AR and 3D Data Qualification on Long Urban Pedestrian Displacements},
  booktitle = {IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct)},
  publisher = {IEEE},
  year = {2017},
  pages = {168-169},
  url = {http://ieeexplore.ieee.org/document/8088474/},
  doi = {10.1109/ISMAR-Adjunct.2017.57}
}
Abid M, Renaudin V, Robert T, Aoustin Y and Le-Carpentier E (2017), "A human-like walking gait simulator for estimation of selected gait parameters", In 14th Workshop on Positioning, Navigation and Communications (WPNC). Bremen, Germany, October, 2017. , pp. 1-6. IEEE.
Abstract: Pedestrian dead reckoning (PDR) is one of the most employed strategies to process inertial signals collected with a handheld device for autonomous indoor positioning. This strategy is based on step length models that usually combine step characteristics with some physiological parameters. These models are calibrated with experimental data for each user. However, many physiological conditions are affecting the walking gait even for steady walking. Therefore, frequent calibration is needed to cope with walking pattern variations. Moreover, PDR models are not adapted to high walking velocities and to the specific walking patterns of some populations like elderly people and pathological cases. In light of these limitations, the modeling of human walking, which considers the induced arm swinging behavior, is needed for improving self-contained inertial indoor navigation. In this paper, a human-like walking model is developed in order to represent and study the correlations between the hand acceleration and gait characteristics. Experimental data were collected from motion capture experiments on one healthy subject in order to validate the model. Results show that the model fitted to the test subject reproduces the walking features found in experiments, as well as the same tendencies in function of the walking velocity.
BibTeX:
@inproceedings{Abid2017a,
  author = {Abid, Mahdi and Renaudin, Valerie and Robert, Thomas and Aoustin, Yannick and Le-Carpentier, Eric},
  title = {A human-like walking gait simulator for estimation of selected gait parameters},
  booktitle = {14th Workshop on Positioning, Navigation and Communications (WPNC)},
  publisher = {IEEE},
  year = {2017},
  pages = {1-6},
  url = {http://ieeexplore.ieee.org/document/8250063/},
  doi = {10.1109/WPNC.2017.8250063}
}
Taia-Alaoui F, Renaudin V and Betaille D (2017), "Points of interest detection for map-aided PDR in combined outdoor-indoor spaces", In International Conference on Indoor Positioning and Indoor Navigation (IPIN). Sapporo, Japan, September, 2017. , pp. 1-8. IEEE.
Abstract: Complementary data are necessary to bind the positioning error growth of Pedestrian Dead Reckoning (PDR). In this paper, absolute position updates are made possible with the online detection of different types of points of interest (POIs) located on the map. The POIs are selected depending on specific motion patterns which are associated to absolute locations on the map. To create the POIs database, the correlation between pedestrian motion and different map locations is first studied and the outcome is a typology of POIs. A K-NN (K nearest neighbors) algorithm is used to train different motion modes, which are further exploited for the detection of POIs in order to update the PDR algorithm with position data. Experimental assessment of the POI-based PDR calibration is conducted in both outdoor and indoor spaces with a focus on the transition between both environments. 90% of the time, motion is correctly classified and the PDR position is corrected with an accuracy that depends on POIs features (width of corridor/door, staircase size...). Therefore, the approach is found to be promising for enhancing PDR positioning using only map data.
BibTeX:
@inproceedings{Alaoui2017,
  author = {Taia-Alaoui, Fadoua and Renaudin, Valerie and Betaille, David},
  title = {Points of interest detection for map-aided PDR in combined outdoor-indoor spaces},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {IEEE},
  year = {2017},
  pages = {1-8},
  url = {http://ieeexplore.ieee.org/document/8115886/},
  doi = {10.1109/IPIN.2017.8115886}
}
Le Scornec J, Ortiz M and Renaudin V (2017), "Foot-mounted pedestrian navigation reference with tightly coupled GNSS carrier phases, inertial and magnetic data", In International Conference on Indoor Positioning and Indoor Navigation (IPIN). Sapporo, Japan, September, 2017. (September), pp. 1-8. IEEE.
Abstract: Many indoor navigation systems have been developed for pedestrians and assessing their performances is a real challenge. Benefiting from a reference solution that is accurate enough to evaluate other indoor navigation systems and assist novel research is of prime interest. The design and algorithms of a foot-mounted reference navigation system titled PERSY (PEdestrian Reference SYstem) are presented in this paper. Quasi static phases of the acceleration and the magnetic field are used to mitigate inertial sensor errors in indoor spaces. Differential indoor/outdoor GNSS phase measurements are added to the strapdown EKF to improve the positioning accuracy with a correlation between low and high frequency velocity estimates. Experiments conducted with four persons over a 1.4 km walking distance show a 0.22% positioning mean error.
BibTeX:
@inproceedings{LeScornec2017,
  author = {Le Scornec, Julien and Ortiz, Miguel and Renaudin, Valerie},
  title = {Foot-mounted pedestrian navigation reference with tightly coupled GNSS carrier phases, inertial and magnetic data},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {IEEE},
  year = {2017},
  number = {September},
  pages = {1-8},
  url = {http://ieeexplore.ieee.org/document/8115882/},
  doi = {10.1109/IPIN.2017.8115882}
}
Antigny N, Servieres M and Renaudin V (2017), "Pedestrian track estimation with handheld monocular camera and inertial-magnetic sensor for urban augmented reality", In International Conference on Indoor Positioning and Indoor Navigation (IPIN). Sapporo, Japan, September, 2017. (September), pp. 1-8. IEEE.
Abstract: Urban environment constitutes a challenging area for pedestrian navigation. However, with the recent increase of pedestrians owning devices (e.g. smartphones), complementary data provided by integrated low cost sensors (camera, Inertial and Magnetic Measurement Unit and GNSS receiver) may be used in a coupling process to accurately estimate the pose (i.e. 3D position and 3D orientation) of a handheld device. Additionally, the actual development and availability of 3D GIS content constitutes a mine of data usable for camera pose estimation. In the context of pedestrian navigation in urban environment, to update a Pedestrian Dead-Reckoning process and to improve the positioning accuracy, we propose to fuse the pose estimated through a vision process thanks to a precisely known 3D model with inertial and magnetic measurements. Experimental data collected in an urban environment, on a long pedestrian path with sparse known models permit to validate the benefit of sensors fusion process. This results in an improved positioning accuracy that enhances the Pedestrian Dead-Reckoning process and enables to display 3D information in Augmented Reality. Performance are presented in terms of positioning accuracy and compared to commonly used solutions.
BibTeX:
@inproceedings{Antigny2017,
  author = {Antigny, Nicolas and Servieres, Myriam and Renaudin, Valerie},
  title = {Pedestrian track estimation with handheld monocular camera and inertial-magnetic sensor for urban augmented reality},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {IEEE},
  year = {2017},
  number = {September},
  pages = {1-8},
  url = {http://ieeexplore.ieee.org/document/8115934/},
  doi = {10.1109/IPIN.2017.8115934}
}
Inderst F, Pascucci F and Renaudin V (2017), "PDR and GPS trajectory parts matching for an improved self-contained personal navigation solution with handheld device", In European Navigation Conference (ENC). Lausanne, Switzerland, May, 2017. , pp. 100-107. IEEE.
Abstract: The evolution of smartphones and their embedded sensors motivates research toward the development of handheld device based navigation solutions especially for harsh environments. In this context, Pedestrian Dead Reckoning is usually adopted to compute the pedestrian's trajectory. Step/stride lengths and walking directions are combined in a recursive process. Unfortunately the estimated path suffers from drifting errors due to the sensors' nature and the motion complexity. To reduce this error, map matching strategies are studied and several solutions are proposed in the literature. In this work a Matching Filter is proposed to mitigate the drifting errors. The Matching Filter is a nest filter based on an Extended Kalman Filter and a Complementary filter. The key idea is to match the PDR trajectory with the standalone GPS trajectory during opportune phases in order to estimate a global heading and scale factor errors on the PDR path. The proposed strategy is tested with a 1km walk in a shopping center. A 75% improvement is found as compared to the PDR only trajectory.
BibTeX:
@inproceedings{Inderst2017,
  author = {Inderst, Federica and Pascucci, Federica and Renaudin, Valerie},
  title = {PDR and GPS trajectory parts matching for an improved self-contained personal navigation solution with handheld device},
  booktitle = {European Navigation Conference (ENC)},
  publisher = {IEEE},
  year = {2017},
  pages = {100-107},
  url = {http://ieeexplore.ieee.org/document/7954198/},
  doi = {10.1109/EURONAV.2017.7954198}
}
Taia-Alaoui F, Betaille D and Renaudin V (2017), "Pedestrian dead reckoning navigation with the help of A*-based routing graphs in large unconstrained spaces", Wireless Communications and Mobile Computing. Vol. 2017, pp. 1-10.
Abstract: An A*-based routing graph is proposed to assist PDR indoor and outdoor navigation with handheld devices. Measurements are provided by inertial and magnetic sensors together with a GNSS receiver. The novelty of this work lies in providing a realistic motion support that mitigates the absence of obstacles and enables the calibration of the PDR model even in large spaces where GNSS signal is unavailable. This motion support is exploited for both predicting positions and updating them using a particle filter. The navigation network is used to correct for the gyro drift, to adjust the step length model and to assess heading misalignment between the pedestrian’s walking direction and the pointing direction of the handheld device. Several datasets have been tested and results show that the proposed model ensures a seamless transition between outdoor and indoor environments and improves the positioning accuracy. The drift is almost cancelled thanks to heading correction in contrast with a drift of 8% for the nonaided PDR approach. The mean error of filtered positions ranges from 3 to 5 m.
BibTeX:
@article{Alaoui2017a,
  author = {Taia-Alaoui, Fadoua and Betaille, David and Renaudin, Valerie},
  title = {Pedestrian dead reckoning navigation with the help of A*-based routing graphs in large unconstrained spaces},
  journal = {Wireless Communications and Mobile Computing},
  year = {2017},
  volume = {2017},
  pages = {1-10},
  url = {https://www.hindawi.com/journals/wcmc/2017/7951346/},
  doi = {10.1155/2017/7951346}
}
Renaudin V and Ortiz M (2017), "Procédé de sélection d'algorithmes de détermination de la trajectoire, programme et dispositifs pour sa mise en œuvre". Thesis at: IFSTTAR.
Abstract: Un système de mesure (10) comprenant un accéléromètre (33) et un gyromètre (34) est configuré pour être fixé de façon détachable à une pluralité de supports (120). Un élément de guidage (122) prévu sur chaque support (120) comprend un ensemble de reliefs (123, 123') qui est différent pour chaque support (120). Dans un exemple, le procédé comprend une étape de détection comprenant le fait de détecter un mouvement comprenant une rotation du système de mesure par rapport au support qui est définie par l'élément de guidage (122), et de détecter la venue en contact, durant la rotation, de l'élément de coopération (111) avec l'ensemble de reliefs (123, 123'), et une étape de sélection comprenant le fait de sélectionner l'algorithme de détermination de trajectoire en fonction de l'ensemble de reliefs (123, 123') avec lequel l'élément de coopération (111) est venu en contact.
BibTeX:
@patent{Renaudin2017a,
  author = {Renaudin, Valérie and Ortiz, Miguel},
  title = {Procédé de sélection d'algorithmes de détermination de la trajectoire, programme et dispositifs pour sa mise en œuvre},
  school = {IFSTTAR},
  year = {2017},
  url = {https://data.inpi.fr/brevets/FR3071052?q=#FR3071052}
}
Renaudin V and Combettes C (2017), "Procédé de détermination de la trajectoire d'un objet mobile, programme et dispositif aptes a la mise en œuvre de ce procédé". Thesis at: IFSTTAR. INPI.
Abstract: Un procédé de détermination d'une trajectoire d'un objet mobile comprenant l'acquisition d'un vecteur accélération et d'un vecteur vitesse angulaire de l'objet mobile, d'un vecteur champ magnétique local au niveau de l'objet mobile, et d'une phase d'un signal émis par un système mondial de navigation par satellite, et une étape de détermination d'un état de position de l'objet mobile à l'aide d'un filtre de Kalman étendu. Un état du filtre de Kalman étendu comprend un vecteur vitesse instantanée et un vecteur vitesse moyenne de l'objet mobile et un décalage entre l'horloge du récepteur satellitaire et le temps du système mondial de navigation par satellite. Le vecteur vitesse moyenne est une moyenne des vecteurs vitesse instantanée de au moins N = fIMU/fGNSS états précédents du filtre de Kalman étendu.
BibTeX:
@patent{Renaudin2017,
  author = {Renaudin, Valérie and Combettes, Christophe},
  title = {Procédé de détermination de la trajectoire d'un objet mobile, programme et dispositif aptes a la mise en œuvre de ce procédé},
  publisher = {INPI},
  school = {IFSTTAR},
  year = {2017},
  url = {https://data.inpi.fr/brevets/FR3070515?q=FR3070515#FR3070515}
}
Ortiz M, De Sousa M and Renaudin V (2017), "A New PDR Navigation Device for Challenging Urban Environments", Journal of Sensors. Vol. 2017, pp. 1-11.
Abstract: The motivations, the design, and some applications of the new Pedestrian Dead Reckoning (PDR) navigation device, ULISS (Ubiquitous Localization with Inertial Sensors and Satellites), are presented in this paper. It is an original device conceived to follow the European recommendation of privacy by design to protect location data which opens new research toward self-contained pedestrian navigation approaches. Its application is presented with an enhanced PDR algorithm to estimate pedestrian’s footpaths in an autonomous manner irrespective of the handheld device carrying mode: texting or swinging. An analysis of real-time coding issues toward a demonstrator is also conducted. Indoor experiments, conducted with 3 persons, give a 5.8% mean positioning error over the 3 km travelled distances.
BibTeX:
@article{Ortiz2017,
  author = {Ortiz, Miguel and De Sousa, Mathieu and Renaudin, Valerie},
  title = {A New PDR Navigation Device for Challenging Urban Environments},
  journal = {Journal of Sensors},
  year = {2017},
  volume = {2017},
  pages = {1-11},
  url = {https://www.hindawi.com/journals/js/2017/4080479/},
  doi = {10.1155/2017/4080479}
}
Taia Alaoui F, Betaille D and Renaudin V (2016), "A multi-hypothesis particle filtering approach for pedestrian dead reckoning", In International Conference on Indoor Positioning and Indoor Navigation (IPIN). Madrid, Spain, October, 2016. , pp. 1-8.
Abstract: A Map aided Pedestrian Dead Reckoning (PDR) algorithm is proposed to mitigate the drift errors and step detection limitations of pedestrian dead reckoning algorithm with handheld sensors in indoor and outdoor spaces. Specific to this context is the changing lever-arm between the handheld device and the pedestrian center of mass that introduces a misalignment between the inertial sensors and the walking directions. To address these challenges, an adaptive routing graph is built based on possible pedestrian's motions, which depend on personal mobility profile and surroundings. An adaptive decision process is also developed to fuse map data with GNSS positions and PDR outputs in a particle filter. The performance is assessed with 1km walk experiments. Main contributions are (1) the calibration of the PDR step length model using both GNSS and map data during straight line travels with miss/over-detected steps modeled by the particle filter; (2) the estimation of angular misalignment between the walking and the handheld unit pointing directions in geometrically constrained areas; (3) a dynamic choice of opportune periods and measurements to calibrate the PDR outputs and improve the positioning process.
BibTeX:
@inproceedings{Alaoui2016,
  author = {Taia Alaoui, Fadoua and Betaille, David and Renaudin, Valerie},
  title = {A multi-hypothesis particle filtering approach for pedestrian dead reckoning},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  year = {2016},
  pages = {1-8},
  url = {https://hal.archives-ouvertes.fr/hal-01451509},
  doi = {10.1109/IPIN.2016.7743614}
}
Renaudin V, Dommes A and Guilbot M (2016), "Engineering, human and legal challenges of navigation systems for personal mobility", IEEE Transaction on Intelligent Transportation Systems., May, 2016. Vol. 18, pp. 177-191.
Abstract: Walking is now promoted as an alternative transport mode to polluting cars and as a successful means to improve health and longevity. Intelligent transport systems navigation services are now directly targeting travelers due to smartphones and their embedded sensors. However, after a decade of research, no universal personal navigation system has been successfully introduced and adopted to improve personal mobility. An analysis of the underlying reasons is conducted, looking at the engineering, human, ethical, and legal challenges. First, contrary to adopting classical mechanization equations linked to solid state physics, location technologies must address complex personal dynamics using connected objects. Second, human factors are often not sufficiently considered while designing new technologies. The needs and abilities of travelers are not systematically addressed from a user-centered perspective. Finally, people want to benefit from location-based services without sharing personal location data to uncontrolled third bodies. Europe is a pioneer in the protection of individuals from personal identification through data processing since location data has been recognized as personal data, but the challenges to enforce the regulation are numerous. The recommendation of “privacy by design and default” is an interesting key to conceive the universal personal navigation solution. Alternative solutions are highlighted, but they definitively require a more interdisciplinary conception.
BibTeX:
@article{Renaudin2016,
  author = {Renaudin, Valérie and Dommes, Aurélie and Guilbot, Michèle},
  title = {Engineering, human and legal challenges of navigation systems for personal mobility},
  journal = {IEEE Transaction on Intelligent Transportation Systems},
  year = {2016},
  volume = {18},
  pages = {177-191},
  url = {https://ieeexplore.ieee.org/abstract/document/7480831},
  doi = {10.1109/TITS.2016.2563481}
}
Kumar S, Renaudin V, Aoustin Y, Le-Carpentier E and Combettes C (2016), "Model - based and Experimental Analysis of the Symmetry in Human Walking in Different Device Carrying Modes", In 6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob). UTown, Singapore , pp. 1172-1179. IEEE.
Abstract: The advent of embedded sensors and their low cost integration in handheld devices (e.g. smartphones) are making them increasingly aware of the human location and context. There have been attempts to extract certain gait features (e.g. step length, step frequency etc.) based on data recorded from handheld devices. However, these attempts have been mostly inspired from observations in biomechanics. Hence, there is a profound need to study the modeling of human walking gait cycle while taking into account the different device carrying modes. It is hypothesized that the presence of handheld device in one hand can alter the step level symmetry of human walking gait cycle without affecting the stride level symmetry. The aim of this paper is to present a model of human walking gait cycle in different device carrying modes over a stride, which is based on parametric optimization technique used in robotics motion generation and the results of a preliminary experimentation conducted using motion capture technology. Both simulation and pilot experiments confirm that the presence of a small mass in one hand can affect the step level symmetry of the human walking gait which constitutes the novel outcome of this paper. Overall, the model successfully captures human walking features and can stand useful for the enhancement of existing pedestrian navigation algorithms with handheld devices for an increased autonomy of elderly people and pedestrian's mobility in general.
BibTeX:
@inproceedings{Kumar2016,
  author = {Kumar, Shivesh and Renaudin, Valerie and Aoustin, Yannick and Le-Carpentier, Eric and Combettes, Christophe},
  title = {Model - based and Experimental Analysis of the Symmetry in Human Walking in Different Device Carrying Modes},
  booktitle = {6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)},
  publisher = {IEEE},
  year = {2016},
  pages = {1172-1179},
  url = {https://ieeexplore.ieee.org/document/7523790},
  doi = {10.1109/BIOROB.2016.7523790}
}
Combettes C and Renaudin V (2016), "Delay Kalman Filter to estimate the attitude of a mobile object with indoor magnetic field gradients", Micromachines. Vol. 7(5), pp. 17p.
Abstract: More and more services are based on knowing the location of pedestrians equipped with connected objects (smartphones, smartwatches, etc.). One part of the location estimation process is attitude estimation. Many algorithms have been proposed but they principally target open space areas where the local magnetic field equals the Earth's field. Unfortunately, this approach is impossible indoors, where the use of magnetometer arrays or magnetic field gradients has been proposed. However, current approaches omit the impact of past state estimates on the current orientation estimate, especially when a reference field is computed over a sliding window. A novel Delay Kalman filter is proposed in this paper to integrate this time correlation: the Delay MAGYQ. Experimental assessment, conducted in a motion lab with a handheld inertial and magnetic mobile unit, shows that the novel filter better estimates the Euler angles of the handheld device with an 11.7° mean error on the yaw angle as compared to 16.4° with a common Additive Extended Kalman filter.
BibTeX:
@article{Combettes2016,
  author = {Combettes, Christophe and Renaudin, Valérie},
  title = {Delay Kalman Filter to estimate the attitude of a mobile object with indoor magnetic field gradients},
  journal = {Micromachines},
  year = {2016},
  volume = {7},
  number = {5},
  pages = {17p},
  url = {https://hal.archives-ouvertes.fr/hal-01357507/document},
  doi = {10.3390/mi7050079}
}
Chable S and Renaudin V (2016), "Couplage de mesures GPS et inertielles pour de la navigation pédestre dans les bâtiments", XYZ. Vol. 146, pp. 27-32.
Abstract: Developing a precise estimation system of pedestrian tracks inside buildings in order to qualify others navigation methods is targeted in this project. The aim of this contribution is to improve the existing solution thanks to novel GNSS observations. GNSS based velocity estimate was studied using two different observations: Doppler frequency and Time-Differenced Carrier-Phase (TDCP). Following a performance comparison of the velocity estimated with both observables, the TDCP was chosen for the hybridization filter. The contribution of GNSS TDCP is found to be significant on the existing solution. Achieving a better biases estimate improves the overall quality of pedestrian foot tracks estimation.
BibTeX:
@article{Chable2016,
  author = {Chable, Sylvain and Renaudin, Valérie},
  title = {Couplage de mesures GPS et inertielles pour de la navigation pédestre dans les bâtiments},
  journal = {XYZ},
  year = {2016},
  volume = {146},
  pages = {27-32},
  url = {https://www.aftopo.org/download.php?type=pdf&matricule=aHR0cHM6Ly93d3cuYWZ0b3BvLm9yZy93cC1jb250ZW50L3VwbG9hZHMvYXJ0aWNsZXMvcGRmL2FydGljbGU0MTQ2MDYucGRm}
}
Antigny N, Servières M and Renaudin V (2016), "Hybrid Visual and Inertial Position and Orientation Estimation based on Known Urban 3D Models", In International conference on Indoor Positioning and Indoor Navigation (IPIN). Madrid, Spain (October), pp. 4-7.
Abstract: More and more pedestrians own devices (as a smartphone) that integrate a wide array of low-cost sensors (camera, IMU, magnetometer and GNSS receiver). GNSS is usually used for pedestrian localization in urban environment, but signal suffers of an inaccuracy of several meters. In order to have a more accurate localization and improve pedestrian navigation and urban mobility, we present a method for city-scale localization with a handheld device. Our central idea is to estimate the 3D location and 3D orientation of the phone camera based on the knowledge of the street furnitures, which have a high repeatability and a large coverage area in the city. Firstly, the use of inertial measurements acquired with an IMU in the vision based method allows to accelerate the calculation of the position and orientation. Secondly, the weighted fusion between the rotation matrices calculated with the vision and the inertial processes allows to give the more importance in the calculation with the highest confidence. With a good points selection, this provides a localization that is in the GNSS post-processed measurement precision use for determining the position and the orientation of the street furnitures. Performances are presented in terms of accuracy of positioning. The final aim is to have with our method a precision good enough to be able to propose in future works a on site display in augmented reality.
BibTeX:
@inproceedings{Antigny2016,
  author = {Antigny, Nicolas and Servières, Myriam and Renaudin, Valérie},
  title = {Hybrid Visual and Inertial Position and Orientation Estimation based on Known Urban 3D Models},
  booktitle = {International conference on Indoor Positioning and Indoor Navigation (IPIN)},
  year = {2016},
  number = {October},
  pages = {4-7},
  url = {https://ieeexplore.ieee.org/abstract/document/7743619},
  doi = {10.1109/IPIN.2016.7743619}
}
Combettes C and Renaudin V (2015), "Comparison of Misalignment Estimation Techniques Between Handheld Device and Walking Directions", In International Conference on Indoor Positioning and Indoor Navigation (IPIN). Banff, Canada , pp. 13-16. IEEE.
Abstract: Pedestrian navigation systems based on smartphone are experiencing fast progress in indoor environment. Pedestrian dead reckoning approaches combined with improved inertial sensors' quality and the exploitation of magnetic field are used to mitigate the sensor drifts. The last remaining issue is related to the hand dynamic. It consists in estimating the angular misalignment between the smartphone pointing direction and the walking direction. Even though, some methods exist, their performances are lacking accuracy and reliability. A comparison of the three main methods to estimate this angular misalignment is performed. These methods are based on Principal Component Analysis (PCA), Forward and Lateral Accelerations Modeling (FLAM) and Frequency analysis of Inertial Signals (FIS). Despite better results for the FIS method all algorithm suffer from large outliers and a need for improved robustness is identified.
BibTeX:
@inproceedings{Combettes2015,
  author = {Combettes, Christophe and Renaudin, Valerie},
  title = {Comparison of Misalignment Estimation Techniques Between Handheld Device and Walking Directions},
  booktitle = {International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  publisher = {IEEE},
  year = {2015},
  pages = {13-16},
  url = {https://ieeexplore.ieee.org/abstract/document/7346766/},
  doi = {10.1109/IPIN.2015.7346766}
}
Renaudin V (2015), "Personal navigation with handheld devices".
Abstract: Contenu du cours: Contexte du système de navigation inertielle (INS), le défi de la navigation personnelle avec un appareil portable et les stratégies de positionnement alternatives
BibTeX:
@misc{Renaudin2015,
  author = {Renaudin, Valérie},
  title = {Personal navigation with handheld devices},
  year = {2015},
  pages = {82 p.},
  url = {https://hal.archives-ouvertes.fr/hal-02907176}
}
Renaudin V, Combettes C and Peyret F (2014), "Quaternion Based Heading Estimation with Handheld MEMS in Indoor Environments", In Position Location And Navigation Conference. Monterey, CA, USA, May, 2014. , pp. 12p.
Abstract: Pedestrian Dead-Reckoning (PDR) is the prime candidate for autonomous navigation with self-contained sensors. Nevertheless with noisy sensor signals and high hand dynamics, estimating accurate attitude angles remains a challenge for achieving long term positioning accuracy. A new attitude estimation algorithm based on a quaternion parameterization directly in the state vector and two opportunistic updates, i.e. magnetic angular rate update and acceleration gradient update, is proposed. The benefit of this method is assessed both at the theoretical level and at the experimental level. The error on the heading, estimated only with the PDR navigation algorithms, is found to less than 7° after 1 km of walk.
BibTeX:
@inproceedings{Renaudin2014a,
  author = {Renaudin, Valérie and Combettes, Christophe and Peyret, François},
  title = {Quaternion Based Heading Estimation with Handheld MEMS in Indoor Environments},
  booktitle = {Position Location And Navigation Conference},
  year = {2014},
  pages = {12p},
  url = {https://ieeexplore.ieee.org/abstract/document/6851427},
  doi = {10.1109/PLANS.2014.6851427}
}
Peyret F, Bétaille D, Pinana-Diaz C, Toledo-Moreo R, Gomez-Skarmeta AF and Ortiz M (2014), "GNSS autonomous localization: Non-Line-Of-Sight satellite detection based on digital maps of city environments", IEEE Robotics and Automation Magazine., March, 2014. Vol. 21(1), pp. 57-63.
Abstract: One of the main drawbacks of global navigation satellite systems (GNSS) in urban environments is that signals may arrive at the receiver antenna only in non-line-of-sight (NLOS) conditions, leading to biased pseudorange estimates when they are taken for granted by the receiver and, eventually, wrong positioning. This article presents a study on the benefits of using three-dimensional (3-D) maps of cities to decide whether the GNSS signal coming from each tracked satellite is reliable. Based on this principle, two different 3-D maps and two methodologies are presented and compared. The results show the benefits of this approach.
BibTeX:
@article{Peyret2014,
  author = {Peyret, François and Bétaille, David and Pinana-Diaz, Carolina. and Toledo-Moreo, Rafael and Gomez-Skarmeta, Antonio F. and Ortiz, Miguel},
  title = {GNSS autonomous localization: Non-Line-Of-Sight satellite detection based on digital maps of city environments},
  journal = {IEEE Robotics and Automation Magazine},
  year = {2014},
  volume = {21},
  number = {1},
  pages = {57-63},
  url = {https://ieeexplore.ieee.org/document/6740014/},
  doi = {10.1109/MRA.2013.2295944}
}
Renaudin V and Combettes C (2014), "Magnetic, Acceleration Fields and Gyroscope Quaternion (MAGYQ) Based Attitude Estimation with Smartphone Sensors for Indoor Pedestrian Navigation", Sensors. Vol. 14(12), pp. 22864-22890.
Abstract: The dependence of proposed pedestrian navigation solutions on a dedicated infrastructure is a limiting factor to the deployment of location based services. Consequently self-contained Pedestrian Dead-Reckoning (PDR) approaches are gaining interest for autonomous navigation. Even if the quality of low cost inertial sensors and magnetometers has strongly improved, processing noisy sensor signals combined with high hand dynamics remains a challenge. Estimating accurate attitude angles for achieving long term positioning accuracy is targeted in this work. A new Magnetic, Acceleration fields and GYroscope Quaternion (MAGYQ)-based attitude angles estimation filter is proposed and demonstrated with handheld sensors. It benefits from a gyroscope signal modelling in the quaternion set and two new opportunistic updates: magnetic angular rate update (MARU) and acceleration gradient update (AGU). MAGYQ filter performances are assessed indoors, outdoors, with dynamic and static motion conditions. The heading error, using only the inertial solution, is found to be less than 10° after 1.5 km walking. The performance is also evaluated in the positioning domain with trajectories computed following a PDR strategy.
BibTeX:
@article{Renaudin2014,
  author = {Renaudin, Valérie and Combettes, Christophe},
  title = {Magnetic, Acceleration Fields and Gyroscope Quaternion (MAGYQ) Based Attitude Estimation with Smartphone Sensors for Indoor Pedestrian Navigation},
  journal = {Sensors},
  year = {2014},
  volume = {14},
  number = {12},
  pages = {22864-22890},
  url = {https://www.mdpi.com/1424-8220/14/12/22864},
  doi = {10.3390/s141222864}
}
Bétaille D, Peyret F, Ortiz M, Miquel S and Fontenay L (2013), "A new modelling based on urban trenches to improve GNSS positioning Quality of Service in cities", IEEE Intelligent Transportation Systems Magazine. Vol. 5(1), pp. 59-70.
Abstract: Digital maps with 3D data proved to make it possible the determination of Non-Line-Of-Sight (NLOS) satellites in real time, whilst moving, and obtain significant benefit in terms of navigation accuracy. However, such data are difficult to handle with Geographical Information System (GIS) embedded software in real time. The idea developed in this article consists is proposing a method, light in terms of information contents and computation throughput, for taking into account the knowledge of the 3D environment of a vehicle in a city, where multipath phenomena can cause severe errors in positioning solution. This method makes use of a digital map where homogeneous sections of streets have been identified, and classified among different types of urban trenches. This classification is so called: "Urban Trench Model". Not only NLOS satellites can be detected, but also, if needed, the corresponding measurements can be corrected and further used in the positioning solver. The paper presents in details the method and its results on several real test sites, with a demonstration of the gain obtained on the final position accuracy. The benefit of the Urban Trench Model, i.e. the reduction of positioning errors as compared to conventional solver considering all satellites, gets up to an amount between 30% and as much as 70% e.g. in Paris.
BibTeX:
@article{Betaille2013,
  author = {Bétaille, David and Peyret, François and Ortiz, M. and Miquel, Stéphan and Fontenay, Leïla},
  title = {A new modelling based on urban trenches to improve GNSS positioning Quality of Service in cities},
  journal = {IEEE Intelligent Transportation Systems Magazine},
  year = {2013},
  volume = {5},
  number = {1},
  pages = {59-70},
  url = {https://ieeexplore.ieee.org/abstract/document/6565516},
  doi = {10.1109/MITS.2013.2263460}
}
He Z, Renaudin V, Petovello MG and Lachapelle G (2013), "Use of High Sensitivity GNSS Receiver Doppler Measurements for Indoor Pedestrian Dead Reckoning", Sensors. Vol. 13(4), pp. 4303-4326.
Abstract: Dead-reckoning (DR) algorithms, which use self-contained inertial sensors combined with gait analysis, have proven to be effective for pedestrian navigation purposes. In such DR systems, the primary error is often due to accumulated heading drifts. By tightly integrating global navigation satellite system (GNSS) Doppler measurements with DR, such accumulated heading errors can usually be accurately compensated. Under weak signal conditions, high sensitivity GNSS (HSGNSS) receivers with block processing techniques are often used, however, the Doppler quality of such receivers is relatively poor due to multipath, fading and signal attenuation. This often limits the benefits of integrating HSGNSS Doppler with DR. This paper investigates the benefits of using Doppler measurements from a novel direct vector HSGNSS receiver with pedestrian dead-reckoning (PDR) for indoor navigation. An indoor signal and multipath model is introduced which explains how conventional HSGNSS Doppler measurements are affected by indoor multipath. Velocity and Doppler estimated by using direct vector receivers are introduced and discussed. Real experimental data is processed and analyzed to assess the veracity of proposed method. It is shown when integrating HSGNSS Doppler with PDR algorithm, the proposed direct vector method are more helpful than conventional block processing method for the indoor environments considered herein.
BibTeX:
@article{He2013,
  author = {He, Zhe and Renaudin, Valerie and Petovello, Mark G. and Lachapelle, Gerard},
  title = {Use of High Sensitivity GNSS Receiver Doppler Measurements for Indoor Pedestrian Dead Reckoning},
  journal = {Sensors},
  year = {2013},
  volume = {13},
  number = {4},
  pages = {4303-4326},
  url = {https://www.mdpi.com/1424-8220/13/4/4303},
  doi = {10.3390/s130404303}
}
Kamel AM, Renaudin V, Nielsen J and Lachapelle G (2013), "INS Assisted Fuzzy Tracking Loop for GPS-Guided Missiles and Vehicular Applications", International Journal of Navigation and Observation. Vol. 2013, pp. 17.
Abstract: Autonomous Navigation Systems used in missiles and other high dynamic platforms are mostly dependent on the Global Positioning System (GPS). GPS users face limitations in terms of missile high dynamics and signal interference. Receiver’s tracking loops bandwidth requirements to avoid these problems are conflicting. The paper presents a novel signal frequency and phase tracking algorithm for very high dynamic conditions, which mitigates the conflicting choice of bandwidths and reduces tracking loop measurement noise. It exploits the flexibility of fuzzy control systems for directly generating the required Numerically Controlled Oscillator (NCO) tuning frequency using phase and frequency discriminators information and is labeled Fuzzy Frequency Phase Lock Loop (FFPLL). Because Fuzzy Systems can be computationally demanding and an Inertial Navigation System (INS) is often onboard the vehicle, an assisted INS Doppler version has been designed and is also proposed. Assessment of the new GPS tracking method is performed with both simulated and experimental data under jamming conditions. The main enhancements of the proposed system consist in reduced processing time, improved tracking continuity and faster reacquisition time.
BibTeX:
@article{Kamel2013,
  author = {Kamel, Ahmed M. and Renaudin, Valerie and Nielsen, John and Lachapelle, Gerard},
  title = {INS Assisted Fuzzy Tracking Loop for GPS-Guided Missiles and Vehicular Applications},
  journal = {International Journal of Navigation and Observation},
  year = {2013},
  volume = {2013},
  pages = {17},
  url = {https://www.hindawi.com/journals/ijno/2013/750385/},
  doi = {10.1155/2013/750385}
}
Ortiz M, Renaudin V, Peyret F and Bétaille D (2013), "Using a reference vehicle for solving GNSS localization challenges", Inside GNSS. Vol. 8(5), pp. 19p.
Abstract: This three-part article describes the features and applications of the Vehicle for Experimental Research on Trajectories (VERT) as designed and used by the GEOLOC Laboratory at IFSTTAR.
BibTeX:
@article{Ortiz2013,
  author = {Ortiz, Miguel and Renaudin, Valérie and Peyret, François and Bétaille, David},
  title = {Using a reference vehicle for solving GNSS localization challenges},
  journal = {Inside GNSS},
  year = {2013},
  volume = {8},
  number = {5},
  pages = {19p},
  url = {https://insidegnss.com/from-lab-to-road-test/}
}
Peyraud S, Bétaille D, Renault S, Ortiz M, Mougel F, Meizel D and Peyret F (2013), "About Non-Line-Of-Sight satellite detection and exclusion in a 3D map-aided localization algorithm", Sensors. Vol. 13, pp. 829-847.
Abstract: Reliable GPS positioning in city environment is a key issue: actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results.
BibTeX:
@article{Peyraud2013,
  author = {Peyraud, Sébastien and Bétaille, David and Renault, Stéphane and Ortiz, Miguel and Mougel, Florian and Meizel, Dominique and Peyret, François},
  title = {About Non-Line-Of-Sight satellite detection and exclusion in a 3D map-aided localization algorithm},
  journal = {Sensors},
  year = {2013},
  volume = {13},
  pages = {829-847},
  url = {https://www.mdpi.com/1424-8220/13/1/829},
  doi = {10.3390/s130100829}
}
Renaudin V (2013), "Active Transport: A New Challenge for Indoor Positioning", In IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN). pp. 40p.
Abstract: Le positionnement et la navigation à l'intérieur des bâtiments est un élément moteur de la promotion du transport actif.
BibTeX:
@inproceedings{Renaudin2013a,
  author = {Renaudin, Valérie},
  title = {Active Transport: A New Challenge for Indoor Navigation},
  booktitle = {IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
  year = {2013},
  pages = {40p},
  url = {https://hal.archives-ouvertes.fr/hal-02921488}
}
Renaudin V, Demeule V and Ortiz M (2013), "Adaptative Pedestrian Displacement Estimation with a Smartphone for Free Inertial Navigation", In IEEE International Conference on Indoor Positioning and Indoor Navigation. Montbéliard, France, October, 2013. , pp. 916-924.
Abstract: Pedestrian dead reckoning is one of the most promising processing strategies of inertial signals collected with a smartphone for autonomous indoor personal navigation. When the sensors are held in hand, step length models are usually used to estimate the walking distance. They combine stride frequency with a finite number of physiological and descriptive parameters that are calibrated with training data for each person. But even under steady conditions, several physiological conditions are impacting the walking gait and consequently these parameters. Frequent calibration is needed to tune these models prior to relying on free inertial navigation solutions in indoor locations. Two hybridization filters are proposed for calibrating the step length model and estimating the navigation solution. They integrate either GNSS standalone positions or GNSS Doppler depending on the coupling level. A data collection performed with four test subjects show the variations of these parameters for the same person during his journey and effectiveness of the calibration for improving the estimation of walking distances. Thanks to the new filters, the error on the travelled distance gets reduced to 7% with the loosely coupled filter and 2% with the tightly coupled filter.
BibTeX:
@inproceedings{Renaudin2013,
  author = {Renaudin, Valérie and Demeule, Vincent and Ortiz, Miguel},
  title = {Adaptative Pedestrian Displacement Estimation with a Smartphone for Free Inertial Navigation},
  booktitle = {IEEE International Conference on Indoor Positioning and Indoor Navigation},
  year = {2013},
  pages = {916-924},
  url = {https://ieeexplore.ieee.org/document/6817901/},
  doi = {10.1109/IPIN.2013.6817901}
}
Voyer M, Bétaille D and Peyret F (2013), "Amélioration de la position GNSS en ville par la méthode des tranchées urbaines", Géomatique Expert. Vol. 93, pp. 14p.
Abstract: Le système GPS est opérationnel depuis les années quatre-vingt-dix. Il a bouleversé les méthodes de positionnement statique, et permis à une communauté d’utilisateurs très large de faire du positionnement dynamique. Le laboratoire Géoloc de l’IFSTTAR s’intéresse particulièrement aux besoins de positionnement pour la mobilité, qu’elle soit embarquée dans des véhicules ou piétonne. Les applications visées ressortissent au domaine des systèmes de transport intelligents, utilisant un matériel peu onéreux, essentiellement en milieu urbain qui concentre la majorité des futures applications. Mais ce contexte est propice aux perturbations dans la réception des signaux des satellites, qui compliquent la localisation précise des équipements. L’IFSTTAR s’est engagé dans des projets pluriannuels consacrés à la localisation en ville, tels que CityVIP (ANR, 2008-2011) et Inturb (MEDDE, DGITM 2012- 2014). Cet article s’intéresse aux problèmes de localisation GNSS en milieu urbain où la connaissance a priori du bâti est disponible sous la forme d’une base de données numérique.
BibTeX:
@article{Voyer2013,
  author = {Voyer, Maxime and Bétaille, David and Peyret, François},
  title = {Amélioration de la position GNSS en ville par la méthode des tranchées urbaines},
  journal = {Géomatique Expert},
  year = {2013},
  volume = {93},
  pages = {14p},
  url = {https://hal.archives-ouvertes.fr/hal-00921405}
}
Susi M, Renaudin V and Lachapelle G (2013), "Motion Mode Recognition and Step Detection Algorithms for Mobile Phone Users", Sensors. Vol. 13(2), pp. 1539-1562.
Abstract: Microelectromechanical Systems (MEMS) technology is playing a key role in the design of the new generation of smartphones. Thanks to their reduced size, reduced power consumption, MEMS sensors can be embedded in above mobile devices for increasing their functionalities. However, MEMS cannot allow accurate autonomous location without external updates, e.g., from GPS signals, since their signals are degraded by various errors. When these sensors are fixed on the user’s foot, the stance phases of the foot can easily be determined and periodic Zero velocity UPdaTes (ZUPTs) are performed to bound the position error. When the sensor is in the hand, the situation becomes much more complex. First of all, the hand motion can be decoupled from the general motion of the user. Second, the characteristics of the inertial signals can differ depending on the carrying modes. Therefore, algorithms for characterizing the gait cycle of a pedestrian using a handheld device have been developed. A classifier able to detect motion modes typical for mobile phone users has been designed and implemented. According to the detected motion mode, adaptive step detection algorithms are applied. Success of the step detection process is found to be higher than 97% in all motion modes.
BibTeX:
@article{Susi2013,
  author = {Susi, Melania and Renaudin, Valerie and Lachapelle, Gerard},
  title = {Motion Mode Recognition and Step Detection Algorithms for Mobile Phone Users},
  journal = {Sensors},
  year = {2013},
  volume = {13},
  number = {2},
  pages = {1539-1562},
  url = {https://www.mdpi.com/1424-8220/13/2/1539},
  doi = {10.3390/s130201539}
}
Bétaille D, Peyraud S, Mougel F, Renault S, Ortiz M, Meizel D and Peyret F (2012), "Using road constraints to progress in real-time NLOS detection", In IEEE IV Symposium on navigation, perception, accurate positioning and mapping for intelligent vehicles. Alcalá de Henares, June, 2012. , pp. 6p.
Abstract: Using a 3D urban model to forecast satellites visibility in urban contexts in order to monitor GPS localization is the main topic of the present article. A virtual image processing is at the core of this method. A preliminary proof of concept has been presented in IEEE ITST 2011, where the theoretically visible satellites were computed with respect to the true position of the vehicle computed off-line from the data of a much more sophisticated equipment. This article addresses now the closed-loop real-time processing of the method, i.e. using the position estimated by the navigation process itself, under road constraints, with very first promising full-scale test results.
BibTeX:
@inproceedings{Betaille2012,
  author = {Bétaille, David and Peyraud, Sébastien and Mougel, Florian and Renault, Stéphane and Ortiz, Miguel and Meizel, Dominique and Peyret, François},
  title = {Using road constraints to progress in real-time NLOS detection},
  booktitle = {IEEE IV Symposium on navigation, perception, accurate positioning and mapping for intelligent vehicles},
  year = {2012},
  pages = {6p},
  url = {https://ieeexplore.ieee.org/xpl/conhome/6222409/proceeding}
}
Hage R-M, Betaille D, Peyret F and Meizel D (2012), "Unscented Kalman filter for urban network travel time estimation", Procedia - Social and Behavioral Sciences., October, 2012. Vol. 54, pp. 1047-1057. Elsevier BV.
Abstract: To estimate urban network travel time, the classical analytical procedure uses cumulative counts at upstream and downstream locations of links. This procedure is vulnerable in urban networks mainly due to significant flow to and from mid-link sinks and sources. Moreover, most urban network links are only equipped with detectors at their end. Therefore without information on the percentage of turning movement at crossroads, the classical analytical procedure is not applicable. The algorithm proposed and validated in this research estimates urban links travel times based on an unscented Kalman filter (UKF). This algorithm integrates stochastically the vehicle count data from underground loop detectors at the end of every link and the travel times from probe vehicles. The proposed methodology can be used for estimating travel time in real-time. Moreover, with this methodology the number of upstream vehicles as well as the number of mid-link sink/source vehicles is estimated for each link.
BibTeX:
@article{Hage_2012,
  author = {Ré-Mi Hage and David Betaille and François Peyret and Dominique Meizel},
  title = {Unscented Kalman filter for urban network travel time estimation},
  journal = {Procedia - Social and Behavioral Sciences},
  publisher = {Elsevier BV},
  year = {2012},
  volume = {54},
  pages = {1047-1057},
  url = {https://www.sciencedirect.com/science/article/pii/S1877042812042826},
  doi = {10.1016/j.sbspro.2012.09.820}
}
Hage R-M, Bétaille D, Peyret F and Meizel D (2012), "Unscented Kalman filter for estimating urban network travel time", In 15th meeting of the European Working Group on Transportation. Paris, September, 2012. , pp. 10p.
Abstract: To estimate urban network travel time, the classical analytical procedure uses cumulative counts at upstream and downstream locations of links. This procedure is vulnerable in urban networks mainly due to significant flow to and from mid-link sinks and sources. Moreover, most urban network links are only equipped with detectors at their end. Therefore without information on the percentage of turning movement at crossroads, the classical analytical procedure is not applicable. The algorithm proposed and validated in this research estimates urban links travel times based on an unscented Kalman filter (UKF). This algorithm integrates stochastically the vehicle count data from underground loop detectors at the end of every link and the travel times from probe vehicles. The proposed methodology can be used for estimating travel time in real-time. Moreover, with this methodology the number of upstream vehicles as well as the number of mid-link sink/source vehicles is estimated for each link.
BibTeX:
@inproceedings{Hage2012a,
  author = {Hage, Ré-Mi and Bétaille, David and Peyret, F. and Meizel, Dominique},
  title = {Unscented Kalman filter for estimating urban network travel time},
  booktitle = {15th meeting of the European Working Group on Transportation},
  year = {2012},
  pages = {10p},
  url = {https://www.sciencedirect.com/science/article/pii/S1877042812042826},
  doi = {10.1016/j.sbspro.2012.09.820}
}
Hage R-M, Bétaille D, Peyret F, Meizel D and Smal J-C (2012), "Unscented Kalman filter for urban link travel time estimation with mid-link sinks and sources", In IEEE ITS Conference. Anchorage, AK, September, 2012. , pp. 10p.
Abstract: To estimate link travel time, the classical analytical procedure uses vehicles counts at upstream and downstream locations. This procedure is vulnerable in urban networks mainly due to significant flow to and from mid-link sinks and sources. One of the important developments recently done on this topic has yielded to the CUPRITE methodology. This method is derived from the classical analytical procedure. It integrates probe vehicle data to correct deterministically the upstream cumulative plot to match the information of probe vehicles travel times, whilst the downstream cumulative plot is kept unchanged. The algorithm proposed and validated in this research estimates urban links travel times based on an unscented Kalman filter (UKF). This algorithm integrates stochastically the vehicle count data from underground loop detectors at the end of every link and the travel time from probe vehicles. The proposed methodology, which can be used for travel time estimation in real-time, is compared to the classical analytical procedure and to the CUPRITE method in case of mid-link perturbation. Along to its lower sensitivity than CUPRITE, the UKF algorithm makes it possible detection and exclusion of outliers from both data sources.
BibTeX:
@inproceedings{Hage2012,
  author = {Hage, Ré-Mi and Bétaille, David and Peyret, François and Meizel, Dominique and Smal, Jean-Christophe},
  title = {Unscented Kalman filter for urban link travel time estimation with mid-link sinks and sources},
  booktitle = {IEEE ITS Conference},
  year = {2012},
  pages = {10p},
  url = {https://ieeexplore.ieee.org/document/6338675},
  doi = {10.1109/ITSC.2012.6338675}
}
Pinana-Diaz C, Toledo-Moreo R, Gomez-Skarmeta A, Bétaille D and Peyret F (2012), "Elevation-enhanced-map-based GPS Non-Line-Of-Sight detection in urban environments", In IEEE IV Symposium on navigation, perception, accurate positioning and mapping for intelligent vehicles. Alcalá de Henares, June, 2012. , pp. 5p.
Abstract: Global Positioning Systems (GPS) may suffer severe errors in urban environments due to the lack of good coverage and the multipath propagation of the satellite signals caused mostly by buildings. Receivers not always are capable of removing multipath signals, especially when satellites are in non-line-of-sight (NLOS) and there are not the corresponding line-of-sight (LOS) signals to compare with and discriminate the faulty one. This leads to wrong pseudorange measurements and errors in the solution of the position computation. This paper presents a solution to the problem of detecting which GPS signals arrive at the receiver in NLOS, thus enabling multipath- free positioning estimates. To it so, elevation-enhanced maps (EEmaps) that model buildings’ positions and heights are exploited. The description of the EEmaps, the NLOS detection algorithm and the results obtained in a test campaign are presented in the paper.
BibTeX:
@inproceedings{PinanaDiaz2012,
  author = {Pinana-Diaz, Carolina and Toledo-Moreo, Rafael and Gomez-Skarmeta, Antonio and Bétaille, David and Peyret, François},
  title = {Elevation-enhanced-map-based GPS Non-Line-Of-Sight detection in urban environments},
  booktitle = {IEEE IV Symposium on navigation, perception, accurate positioning and mapping for intelligent vehicles},
  year = {2012},
  pages = {5p},
  url = {http://madis-externe.ifsttar.fr/exl-php/DOC00018942}
}
Renaudin V, Susi M and Lachapelle G (2012), "Step Length Estimation Using Handheld Inertial Sensors", Sensors. Vol. 12(7), pp. 8507-8525.
Abstract: In this paper a novel step length model using a handheld Micro Electrical Mechanical System (MEMS) is presented. It combines the user’s step frequency and height with a set of three parameters for estimating step length. The model has been developed and trained using 12 different subjects: six men and six women. For reliable estimation of the step frequency with a handheld device, the frequency content of the handheld sensor’s signal is extracted by applying the Short Time Fourier Transform (STFT) independently from the step detection process. The relationship between step and hand frequencies is analyzed for different hand’s motions and sensor carrying modes. For this purpose, the frequency content of synchronized signals collected with two sensors placed in the hand and on the foot of a pedestrian has been extracted. Performance of the proposed step length model is assessed with several field tests involving 10 test subjects different from the above 12. The percentages of error over the travelled distance using universal parameters and a set of parameters calibrated for each subject are compared. The fitted solutions show an error between 2.5 and 5% of the travelled distance, which is comparable with that achieved by models proposed in the literature for body fixed sensors only.
BibTeX:
@article{Renaudin2012,
  author = {Renaudin, Valérie and Susi, Melania and Lachapelle, Gérard},
  title = {Step Length Estimation Using Handheld Inertial Sensors},
  journal = {Sensors},
  year = {2012},
  volume = {12},
  number = {7},
  pages = {8507-8525},
  url = {https://www.mdpi.com/1424-8220/12/7/8507},
  doi = {10.3390/s120708507}
}
Bétaille D, Nicolle P and Ieng S-S (2010), "Trajectographie Submétrique par Couplage DGPS, Carte Précise des Marquages et Vision", Conférence PRAC, Paris, Mai 2010., In Conférence PRAC. Paris, May, 2010. , pp. 1p.
BibTeX:
@inproceedings{Betaille2010,
  author = {Bétaille, David and Nicolle, Philippe and Ieng, Sio-Song},
  title = {Trajectographie Submétrique par Couplage DGPS, Carte Précise des Marquages et Vision},
  booktitle = {Conférence PRAC},
  journal = {Conférence PRAC, Paris, Mai 2010},
  year = {2010},
  pages = {1p},
  url = {http://prac2010.free.fr/lib/pres/poster_48.pdf}
}
Bétaille D and Toledo-Moreo R (2010), "Creating enhanced maps for lane-level vehicle navigation", IEEE Transactions on ITS. Vol. 11(4), pp. 786-798.
Abstract: The concept of enhanced maps (Emaps) was introduced with one main objective: It should characterize roads, first, with more completeness and, second, with more accuracy than standard maps to fulfill the requirements of new challenging road safety applications and advanced driver-assistance systems (ADAS). This paper introduces a paradigm for Emap definition and creation on which every road lane is represented and topologically connected to the rest of lanes. Following this approach, a number of Emaps have been created in France, Germany, and Sweden. The experiments carried out in these test sites with the Emaps show the capability of our Emap definition to assist with the determination of the vehicle position at the lane level. Details of the processes of extraction and connection of the road segments are given in the core of this paper, as well as a discussion of the elaboration process and future guidelines in the conclusion.
BibTeX:
@article{Betaille2010a,
  author = {Bétaille, David and Toledo-Moreo, Rafael},
  title = {Creating enhanced maps for lane-level vehicle navigation},
  journal = {IEEE Transactions on ITS},
  year = {2010},
  volume = {11},
  number = {4},
  pages = {786-798},
  url = {https://ieeexplore.ieee.org/document/5499153/},
  doi = {10.1109/TITS.2010.2050689}
}
Toledo-Moreo. R, Bétaille D and Peyret F (2010), "Lane level integrity provision for navigation and map-matching with GNSS, dead-reckoning and enhanced maps", IEEE Transactions on ITS., March, 2010. Vol. 11(1), pp. 100-112.
Abstract: Lane-level positioning and map matching are some of the biggest challenges for navigation systems. Additionally, in safety applications or in those with critical performance requirements (such as satellite-based electronic fee collection), integrity becomes a key word for the navigation community. In this scenario, it is clear that a navigation system that can operate at the lane level while providing integrity parameters that are capable of monitoring the quality of the solution can bring important benefits to these applications. This paper presents a pioneering novel solution to the problem of combined positioning and map matching with integrity provision at the lane level. The system under consideration hybridizes measurements from a global navigation satellite system (GNSS) receiver, an odometer, and a gyroscope, along with the road information stored in enhanced digital maps, by means of a multiple-hypothesis particle-filter-based algorithm. A set of experiments in real environments in France and Germany shows the very good results obtained in terms of positioning, map matching, and integrity consistency, proving the feasibility of our proposal.
BibTeX:
@article{ToledoMoreo2010,
  author = {Toledo-Moreo., Rafael and Bétaille, David and Peyret, François},
  title = {Lane level integrity provision for navigation and map-matching with GNSS, dead-reckoning and enhanced maps},
  journal = {IEEE Transactions on ITS},
  year = {2010},
  volume = {11},
  number = {1},
  pages = {100-112},
  url = {https://ieeexplore.ieee.org/abstract/document/5286855/},
  doi = {10.1109/TITS.2009.2031625}
}