基于PSO算法的路径规划收敛性与参数分析

Path planning based on PSO algorithm convergence and parameters analysis

提出了一种基于粒子群优化和极坐标变换的移动机器人路径规划方法,采用栅格法的极坐标和直角坐标变换关系对外部环境进行建模,利用粒子群优化算法建立了移动机器人的路径规划方法,指出了基于粒子群优化算法的移动机器人路径规划过程与马尔可夫链关系,并用概率论的方法分析了移动机器人路径规划方法的收敛性,阐明了本方法随均匀分布和正态分布的参数关系与收敛区间.仿真与计算结果证明了该方法对于移动机器人路径规划具有有效性与可行性.

A method for mobile robot path planning was proposed based on particle swarm optimization and coordination transformation method.Using the grid method polar coordinates and the Cartesian coordinate transformation path environment modeling,the particle swarm optimization algorithm for mobile robot path planning method was established.It was found that the particle swarm optimization algorithm for mobile robot path planning process was actually a Markov chain analysis.The probability theory was applied to study the relationship with the parameters and convergence of mobile robot path planning,and convergence interval of the method with uniform distribution and normal distribution were clarified.Simulation and calculation results show the effectiveness of the algorithms and methods for mobile robot path planning.