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

Thibaut Tezenas Du Montcel 1, 2 Amaury Nègre 2, 3 Matthieu Muschinowski 3 Jose-Ernesto Gomez-Balderas 2 Nicolas Marchand 1
1 GIPSA-SYSCO - SYSCO
GIPSA-DA - Département Automatique
2 GIPSA-AGPIG - AGPIG
GIPSA-DIS - Département Images et Signal
3 GIPSA-Services - GIPSA-Services
GIPSA-lab - Grenoble Images Parole Signal Automatique
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.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01910732
Contributor : Nicolas Marchand <>
Submitted on : Thursday, November 1, 2018 - 7:16:32 PM
Last modification on : Thursday, March 7, 2019 - 8:31:19 PM
Long-term archiving on : Saturday, February 2, 2019 - 2:04:01 PM

File

paper20.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01910732, version 1

Citation

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. 10th Workshop on Planning, Perception and Navigation for Intelligent Vehicles at 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 2018, Madrid, Spain. ⟨hal-01910732⟩

Share

Metrics

Record views

132

Files downloads

92