基于混沌灰狼优化的多无人机协同航路规划

Cooperative Path Planning for Multi-UAVs Based on Chaos Gray Wolf Optimization

针对多无人机协同执行饱和攻击任务的时空约束,本文提出了基于混沌灰狼优化的离线航路规划方法,实现了多无人机协同航路的有效生成。首先,针对饱和攻击任务的特点进行分析,将具有时空约束的多无人机同时到达问题转化为协同航程问题;其次,针对将混沌映射引入灰狼优化算法中,提出了混沌灰狼优化算法,以提高原算法的探索能力和收敛速度;最后,提出了基于几何规划的航点扩展策略,从而构造出满足任务攻击时间与攻击方位要求的航点序列。通过对单无人机航路规划问题的仿真验证了改进算法的寻优能力;通过对面向饱和攻击任务的航路规划仿真验证了所提方法的可行性和有效性。

Aiming at the space-time constraints of multi UAVs cooperative execution of saturation attack mission, an off-line path planning method based on chaotic gray wolf optimization(CGWO) is proposed to realize the effective generation of multi UAVs cooperative path. Firstly, according to the characteristics of saturation attack mission, the simultaneous arrival problem of multiple UAVs with space-time constraints is transformed into a cooperative range problem;Secondly, aiming at introducing chaotic mapping into gray wolf optimization algorithm, a chaotic gray wolf optimization algorithm is proposed to improve the exploration ability and convergence speed of the original algorithm;Thirdly, a waypoint expansion strategy based on geometric programming is proposed to construct a waypoint sequence that meets the requirements of mission attack time and attack azimuth;Through the simulation of single UAV path planning problem, the optimization ability of the improved algorithm is verified. The feasibility and effectiveness of the proposed method are verified by path planning simulation for saturation attack mission.