UAV Online Path Planning Based on Improved Genetic Algorithm
Xiaohai Wang, Xiuyun Meng · 2019
When the traditional Genetic Algorithm (GA) is used for unmanned aerial vehicle (UAV) path planning, the shortcomings of local search ability are reflected when the planning time is more urgent. To address this shortcoming, this paper proposes an improved genetic algorithm that limits the new gene's generating region. The generating region of the evolution operator is dynamically adjusted. The algorithm is applied to UAV online path planning for tracking moving target. The simulation results show that the method enhances the local search ability of the algorithm and improves the searching efficiency. UAV online path planning can be completed well with the improved genetic algorithm.