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Sensor-based Autonomous Navigation of Omnidirectional Vehicles Dealing with Collisions and Occlusions in Unknown Environments

Abstract : Navigation tasks are often subject to several constraints that can be related to the sensors (visibility) or come from the environment (obstacles). In this paper, we propose a framework for autonomous omnidirectional vehicles, that takes into account both collision and occlusion risk, during sensor-based navigation. The task consists in driving the vehicle towards a visual target in the presence of static and moving obstacles. The target is acquired by fixed - limited field of view - on-board sensors, while the surrounding obstacles are detected by lidar scanners. To perform the task, the vehicle has not only to keep the target in view while avoiding the obstacles, but also to predict its location in the case of occlusion. The effectiveness of our approach is validated through several experiments.
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https://hal.archives-ouvertes.fr/hal-01625946
Contributor : Andrea Cherubini <>
Submitted on : Monday, October 30, 2017 - 2:58:25 AM
Last modification on : Thursday, July 25, 2019 - 10:18:01 AM
Long-term archiving on: : Wednesday, January 31, 2018 - 12:28:33 PM

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  • HAL Id : hal-01625946, version 1

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Abdellah Khelloufi, Nouara Achour, Robin Passama, Andrea Cherubini. Sensor-based Autonomous Navigation of Omnidirectional Vehicles Dealing with Collisions and Occlusions in Unknown Environments. 2017. ⟨hal-01625946v1⟩

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