基于评估和分工合作并行蚁群机器人路径规划

摘要

In order to efficiently solve the problem of mobile robot' s path planning in complex dynamic environment, proposed a new method which implemented parallel ant colony optimization algorithm based on assessment and division-cooperation of labor. This method consists of control center and independent process unit. Each process unit uses division-cooperation of labor ant colony to optimize the ant search in local and global aspect, and then sends the result to the control center. Control center was responsible for coordinating the result which got from each independent process unit and used the assessment mechanism to make final decision. Simulation result shows that this algorithm is feasible and effective.%针对复杂环境中移动机器人的导航中存在的问题,提出了一种适用于机器人路径规划的并行蚁群分工合作算法.该方法由控制中心和独立的运算单元组成,每个运算单元中使用分工合作的蚁群进行计算从而从局部和全局两个方面优化蚁群的路径搜索,并将计算发送给处于控制中心的计算机,控制中心则负责处理每个运算单元发送的阶段性的路径搜索结果并利用评估机制对每个计算机得出的结果做最后的决策.从仿真结果可以看出该算法是有效且可行的.