一种生物地理学移动机器人路径规划算法

目前,虽然有多种智能计算方法用于移动机器人路径规划问题,但在复杂环境下,多数智能计算方法表现出效率低下,结果较差的问题。提出一种结合基于有效顶点的栅格编码法和改进的生物地理学优化算法的移动机器人路径规划方法,以解决该类问题。结合已知的环境信息,从精英策略、降维机制和基于惯性算子的迁移操作3方面改进了生物地理学优化算法。改进算法用于机器人移动路径,与人工蜂群算法、粒子群算法和人工鱼群算法等智能算法进行比较,实验的结果证实改进算法能够更有效地解决复杂环境下机器人路径规划问题。

A biogeography-based mobile robot path planning algorithm

At present, there are many intelligent computing methods used in mobile robot path planning; however, in complex environments, most of them have low efficiency and poor results. In order to solve such problems, this paper proposes a new method for mobile robot path planning, which combines the grid coding method based on the effective vertex with the improved biogeography-based optimization (BBO). On the basis of the environmental infor-mation that has been learned, the BBO is improved in three aspects:elite strategies, dimension reduction mecha-nisms and migration based on inertial operator. The improved BBO is applied in path planning. The method is com-pared with artificial bee colony (ABC), particle swarm optimization (PSO) and artificial fish algorithm (AFA). Experiment results show that the improved method can solve the problem of mobile robot path planning in a complex environment more efficiently.