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An Egocubemap Based Algorithm for Quadrotors Obstacle Avoidance Using a Single Depth Camera

Abstract : A fast obstacle avoidance algorithm is a necessary condition to enable safe flights of Unmanned Aerial Vehicles (UAVs) eventually at high-speed. Large UAVs usually have a lot of sensors and available computational resources which allow complex algorithms to run fast enough to navigate safely. On the contrary, small UAVs gather many difficulties, like computation and sensors limitations, forcing algorithms to retain only a few keys points of their environment. This paper proposes an obstacle avoidance algorithm for quadrotor using a single depth camera. Taking advantage of the possibilities offered by embedded GPUs, a cubic world representation centered on the robot-called Egocubemap-is used while the whole obstacle detection and avoidance algorithm is light enough to run at 10 Hz on-board. Numerical and experimental validations are provided.
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Submitted on : Thursday, November 1, 2018 - 7:16:32 PM
Last modification on : Monday, November 29, 2021 - 4:27:57 PM
Long-term archiving on: : Saturday, February 2, 2019 - 2:04:01 PM


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  • HAL Id : hal-01910732, version 1


Thibaut Tezenas Du Montcel, Amaury Nègre, Matthieu Muschinowski, Jose-Ernesto Gomez-Balderas, Nicolas Marchand. An Egocubemap Based Algorithm for Quadrotors Obstacle Avoidance Using a Single Depth Camera. IROS 2018 - Workshop on Crossmodal Learning for Intelligent Robotics in conjunction with IEEE/RSJ IROS, Oct 2018, Madrid, Spain. ⟨hal-01910732⟩



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