BOARR : A Benchmark for quadrotor Obstacle Avoidance based on ROS and RotorS

Thibaut Tezenas Du Montcel 1 Amaury Negre 2 Jose-Ernesto Gomez-Balderas 3 Nicolas Marchand 1
1 GIPSA-SYSCO - SYSCO
GIPSA-DA - Département Automatique
2 GIPSA-Services - GIPSA-Services
GIPSA-lab - Grenoble Images Parole Signal Automatique
3 GIPSA-AGPIG - AGPIG
GIPSA-DIS - Département Images et Signal
Abstract : Multiple obstacle avoidance algorithms have been proposed over the past years but they were not tested using a common protocol. Some were tested statistically by repeating a task in specific simulated worlds. Others went through a number of real handmade obstacles. The last ones did lengthy real flights in environments that are tough to characterize. This paper proposes the BOARR benchmark that aims to give a common framework to test and compare obstacle avoidance algorithms for quadrotors. It offers multiple sensors and multiple indicators relevant to all quadrotor obstacle avoidance algorithms. It uses ROS, Gazebo and RotorS and can be easily deployed.
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https://hal.archives-ouvertes.fr/hal-02142571
Contributor : Thibaut Tezenas Du Montcel <>
Submitted on : Tuesday, May 28, 2019 - 4:56:21 PM
Last modification on : Monday, January 13, 2020 - 1:13:08 AM

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Thibaut Tezenas Du Montcel, Amaury Negre, Jose-Ernesto Gomez-Balderas, Nicolas Marchand. BOARR : A Benchmark for quadrotor Obstacle Avoidance based on ROS and RotorS. 2019. ⟨hal-02142571⟩

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