一种基于优化融合算法的机器人路径规划技术

A Mobile Robot Path Planning Technology Based on Optimization Fusion Algorithm

局部最优问题是当前移动机器人路径规划算法中存在的一个关键问题.为了解决该问题,文章提出了一种基于PSO和QGA的移动机器人路径规划算法.该算法利用粒子群具有记忆能力、能参考局部最佳位置方向和全局最佳位置方向进行择优搜索的特点,对路径进行局部优化;然后利用量子遗传算法的收敛速度快和全局寻优能力强的特点,对最优或次优个体进行选择,为最优或次优个体进入下一代提供了保障,提高了算法的性能.仿真结果表明,该算法的稳定性及寻优能力均被明显改善,且有更好的收敛性以及更强的连续空间搜索能力,适合于求解复杂优化问题.

Local optimum is a key problem in current research related mobile robot path planning methods .In order to solve the problem , a novel mobile robot path planning algorithm is proposed in this paper ,which uses memory ability ,the ability of the best position ＆amp; direction investigation of the individual and the global of particle swarm optimization （PSO） to plan path locally for mobile robot ,and uses fast conver‐gence ＆amp; searching the best solution capability of quantum genetic algorithm （QGA） to select the optimal or sub‐optimal path in order to protect the optimal or sub‐optimal path into the next generation .It increases greatly the efficiency of the algorithm .Results of the simulation demon‐strate the ability of finding the best solution and the stability of this method are greatly improved ,it has better convergent property and ability of searching more extensive space and is fit for finding the solution in complex optimization problems .