基于免疫克隆粒子群算法的无人机航迹规划

Path Planning for UAV Based on Immune Clone Particle Swarm Optimization

针对无人机飞行中可能遭遇突发移动威胁的情况,为了提高无人机路径规划的安全性和快速性,文中提出基于免疫克隆粒子群算法的航迹规划策略。该策略在标准粒子群算法中,结合变结构优化搜索理论,引入免疫克隆优化搜索。与同类路径规划算法的对比仿真发现,该策略有效改善粒子群算法的局部和全局搜索能力。仿真结果表明,文中提出的规划策略,满足无人机航迹规划需求,且在速度和安全性能两方面较其他算法更优。

In view of emergent moving threats to improve security and velocity of path planning of UAV, this paper proposed a dynamic path planning strategy of immune clone particle swarm optimization algorithm. The immune clone optimization search was added to the standard particle swarm optimization （PSO） algorithm. In addition, a variable structure optimization search theory was presented. Compared with other path planning algorithms, this strategy has improved the ability of local and global search of PSO. The simulation shows that this planning strategy meets the needs of practical application. Moreover,we conclude that the improved PSO prodeces superior trajectories to other algo- rithms.