基于改进粒子群优化算法的移动机器人路径规划

摘要

To get an optimal smooth path for a micro soccer robot, a novel path planning approach using improved particle swarm optimization is proposed with a path description by string of Ferguson splines. The path planning is then equivalent to optimization of parameters of particular cubic Ferguson splines. The improved Particle Swarm Optimization with Velocity Mutation (VMPSO) is introduced to optimize the path for its fast convergence and global search character. Experimental results prove the rationality and great practical value of the proposed algorithm, which can get convergence within 80 iterations, with a collision-avoiding smooth optimal path being planned fleetly.%为了实现微型足球机器人的平滑最优路径规划,提出了一种结合Ferguson样条路径描述和改进粒子群优化算法的路径规划方法.利用Ferguson样条描述移动机器人路径,将路径规划问题转化为三次样条曲线的参数优化问题,借助改进的具有速度变异的粒子群算法进行路径优化.仿真实验表明,算法可以有效进行障碍环境下机器人的无碰撞路径规划,改进的粒子群算法进行路径优化迭代80次左右即可收敛,规划路径平滑、合理,有一定的实用价值.