This paper deals with the path planning problem of unmanned aerial vehicle (UAV) swarm in the dense-obstacle environment. A novel hierarchical path planning approach with two-level structure is proposed to obtain collision-free and smooth paths for UAV swarm. In the first level, an improved particle swarm optimization (PSO) method is proposed to generate a collision-free global optimal path to determine the overall movement orientation of UAV swarm. In the second level, the improved artificial potential field (APF) combined with consensus theory is used for local path planning of each UAV in the swarm with the turning points extracted from the global optimal path obtained previously as a series of destinations under the leader-follower formation control framework. Numerical simulations are implemented to prove the validity of our proposed algorithm.
Efficient Path Planning for UAV Swarm Under Dense Obstacle Environment
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021
Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021) ; Chapter : 11 ; 101-110
2022-03-18
10 pages
Article/Chapter (Book)
Electronic Resource
English
Mission Planning for Heterogeneous UAVs in Obstacle-Dense Environment
Springer Verlag | 2023
|IEEE | 2020
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