分析了人工势场模型存在的目标不可到达问题(GNRON)和由于局部最优解的存在而产生的死锁问题,提出了一种建立在改进人工势场模型上的基于遗传算法的最优路径搜索方法。仿真结果验证了本模型的有效性,能有效的解决由于人工势场模型缺陷而带来的路径规划问题。
The problems of goals nonreachable with obstacles nearby (GNRON) and dead lock caused by local minimum were described when using potential field methods for mobile robot path planning. Thus, a new way of optimizing the path using improved potential field approach with genetic algorithm was proposed. The results of simulation verify that the new method can solve the problem effectively caused by the defects of the APF model.