Multi-UAV Three-Dimensional Path Planning Based on Improved Grey Wolf Optimization Algorithm
Mingyu Zhang, Feng Liu, Yujie Wang, Yaqing Yan, Zheng-Xian Wei · 2024
To address the challenges of multi-unmanned aerial vehicle (UAV) trajectory planning in three-dimensional complex environments, this study proposes a method based on the Improved Grey Wolf Optimization Algorithm for Multi-UAV 3D Trajectory Planning. The approach simulates real geographical environments, establishing three-dimensional terrain and no-fly zone models. Building upon the foundation of single UAV trajectory planning, the proposed method incorporates collaborative constraints for multi-UAV coordination, forming an evaluation function for multi-UAV collaborative trajectory planning. In order to solve the limitations of the standard Grey Wolf Algorithm, which is prone to local optima and exhibits suboptimal convergence rates, an improved convergence factor strategy and a reward-penalty mechanism in the optimization process are introduced. Comparative evaluations against several relevant algorithms validate the superior feasibility of the proposed approach. Simulation results demonstrate that, compared to other algorithms, the proposed method achieves smaller trajectory costs, faster convergence rates, and more stable performance.