Abstract
In recent years, autonomous vehicles have become an axis of academic and industrial research. Localizing these vehicles without a GPS signal represents a challenge for researchers, because the other sensors are usually less accurate, less fast and require more computation. Among localization methods, dead reckoning ones do not need prior knowledge as they are easier to implement for real time purposes. However, their biggest flaw is the accumulation of errors over time. In this work, we present an onboard localization method dedicated to autonomous vehicles for short time navigation without GPS. We developed a method with a high rate inertial-visual data fusion module that allows locating the vehicle in real-time. This method has been validated offline and tested online in a path following control loop on an experimental vehicle.
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Acknowledgements
Thanks to ANR for financing the Evi-Deep support project. Thanks to Sébastien Jung who worked on the implementation of IO and VO during his internship in 2021. Thanks to the automobile museum that made the experimentation’s circuit available.
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Oubouabdellah, S.N., Bazeille, S., Mourllion, B., Ledy, J. (2023). Localization and Navigation of an Autonomous Vehicle in Case of GPS Signal Loss. In: Theilliol, D., Korbicz, J., Kacprzyk, J. (eds) Recent Developments in Model-Based and Data-Driven Methods for Advanced Control and Diagnosis. ACD 2022. Studies in Systems, Decision and Control, vol 467. Springer, Cham. https://doi.org/10.1007/978-3-031-27540-1_19
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