Distributed path planning for controlling a fleet of UAVs : application to a team of quadrotors

Abstract : In this paper, a distributed trajectory generation strategy is proposed to control a group of Unmanned Aerial Vehicles (UAVs). The issue, treated as an online optimization problem, is solved using a Particle Swarm Optimization (PSO) algorithm. The proposed PSO is implemented independently in each vehicle in order to determine, by minimizing a cost function, the best paths that ensure the eet formation control, target tracking and collision and obstacle avoidance. The method illustrated in this paper offers solutions to several questions related to the control of a group of UAVs and could be applied to solve problems such as covering large search areas for surveillance, inspection and rescue. Firstly, experiments on one quadrotor are implemented to illustrate the effectiveness of the proposed algorithm. Large disturbances and obstacles are considered to illustrate the robustness of the presented approach. The method is tested in a real environment with a group of three quadrotors.
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Communication dans un congrès
20th IFAC World Congress, IFAC 2017, Jul 2017, Toulouse, France. 2017
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Soumis le : vendredi 23 juin 2017 - 18:12:53
Dernière modification le : mardi 24 octobre 2017 - 14:32:07

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  • HAL Id : hal-01537777, version 1

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Adel Belkadi, Hernan Abaunza, Laurent Ciarletta, Pedro Castillo, Didier Theilliol. Distributed path planning for controlling a fleet of UAVs : application to a team of quadrotors. 20th IFAC World Congress, IFAC 2017, Jul 2017, Toulouse, France. 2017. 〈hal-01537777〉

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