In recent years, UAVs have been widely used on the battlefield, showing their great advantages over traditional aircraft. In response to the current hotly researched UAV clustering problem, this paper specifically investigates UAV swarm trajectory planning. Aiming at the problem of multi-UAVs cooperative trajectory planning in complex environments, the trajectory planning of each UAV and the mutual coordination of cluster members are comprehensively considered, and it is transformed into a multi-constrained mathematical problem that can be solved. By adopting a new track point update strategy, the actual practicability of the track is improved. An improved gray wolf optimizer-variable convergence dynamic weight adaptive position adjustment gray wolf optimizer (VCDWAP-GWO) is proposed. The algorithm combines three improved strategies: new convergence factor, Adaptive adjustment of position and dynamic weights. Through the improvement of the algorithm, the convergence speed and accuracy of the algorithm for solving the trajectory planning problem are greatly improved.
Three-Dimensional Collaborative Path Planning for Multi-UAVs Based on Improved GWO
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022
Proceedings of 2022 International Conference on Autonomous Unmanned Systems (ICAUS 2022) ; Chapter : 230 ; 2487-2496
2023-03-10
10 pages
Article/Chapter (Book)
Electronic Resource
English
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