Dynamic 3D Path Planning for UAV Based on Enhanced Grey Wolf Optimization Algorithm

The enhanced grey wolf optimization algorithm is proposed for the path planning problem of UAV in a multi-obstacle and dynamic obstacle environment. Firstly, the population is initialized by combining Tent chaos mapping, secondly, a differential evolution strategy is adopted for the leader grey wolf individuals, and finally, the enhanced grey wolf optimization algorithm and the artificial potential field method are fused to achieve the goal of avoiding dynamic obstacles. The results are tested under the dynamic obstacle model, and it is proved that the enhanced grey wolf optimization algorithm has excellent global search capability and better robustness under the complex environment. The method introduces innovative ideas to the domain of dynamic obstacle avoidance in path planning.