基于改进粒子群优化算法的无人机路径规划研究

Research on UAV Path Planning Based on Improved Particle Swarm Optimization Algorithm

粒子群优化(PSO)算法是一种具有过早收敛和易于停滞的简单方法。在使用PSO解决路径规划问题时,效率损失和次优解决方案经常发生。因此,本文提出了一种通过使用Rauch Tung Striebel(RTS)滤波器来优化影响PSO算法性能参数的方法。此外,使用RTS滤波器消除PSO更新位置的不规则误差,并平滑生成的路径。实验结果表明,该方法基于PSO并结合RTS算法,在无人机路径规划问题的解决方案质量和鲁棒性方面均优于现有方法。

Particle Swarm Optimization(PSO)algorithm is a simple method with premature convergence and easy stagnation.When using PSO to solve path planning problems,efficiency losses and suboptimal solutions often occur.Therefore,this paper proposes a method to optimize the performance parameters of the PSO algorithm by using a Rauch Tung Striebel(RTS)smoother.In addition,an RTS smoother is used to eliminate irregular errors in the PSO update position and smooth the generated path.Experimental results show that this method is based on PSO and RTS algorithm,and it is superior to existing methods in terms of solution quality and robustness of UAV path planning problems.