基于改进混合粒子群优化算法的多无人机协同围捕方法研究

Multi-UAV Cooperative Target Capture Based on Improved Hybrid PSO Algorithm

针对多无人机协同围捕问题,在无人机运动学约束基础上,考虑各无人机应同时到达围捕位置,提出了多机协同围捕任务规划两层求解架构。在任务协调层通过改进混合粒子群优化方法,以各无人机同时到达指定围捕位置的最小时间为目标,优化调度给出多目标围捕方案;在航路规划层考虑无人机初始状态及运动学约束,通过Dubins曲线调整实现各无人机同时到达围捕位置。仿真结果表明了所提方法的有效性。

Aiming at the problem of multi-UAV cooperative target capture,and considering that each UAV reaches the capture position at the same time,a two-layer solution architecture for task planning of multi-UAV cooperative capture is proposed on the basis of UAV kinematics constraints.In the task coordination layer,by improving the hybrid Particle Swarm Optimization(PSO)method and taking the minimum time for each UAV to reach the designated capture point as the goal,the multi-objective capture scheme is given by optimizing the scheduling.In the route planning layer,the initial state and kinematics constraints of UAVs are considered,and Dubins curve is adjusted to realize that each UAV reach the capture position at the same time.Simulation results demonstrate the effectiveness of the proposed method.