UAV Path Planning in 3D Complex Environments Using Genetic Algorithms
Shanshan Leng, Hui Sun · 2021
This paper studies the path planning problem of an unmanned aerial vehicle (UAV) flying in a mountainous region, in which obstacles both on the ground and in the air are included. Two objectives, i.e., minimizing total length and minimizing radar detection threat, are considered in path planning. Two genetic algorithms (GAs) with different population initialization methods and genetic operations are proposed to solve the problem. Computational results show that both algorithms can find safe and flyable paths in three dimensional (3D) complex environments. Furthermore, one of them generally leads to a better performance.