工业机器人最短移动路径智能选取方法仿真

Simulation of Intelligent Selection Method for Shortest Mobile Path of Industrial Robots

对工业机器人移动路径选取问题的研究,能够有效提高工业机器人工作效率。对机器人最短移动路径的智能选取,需要选中一条路径后进行一次搜索,保留其中较优的解,完成路径的选取。传统方法检测周围近距离障碍物,确定临时路径后择优,但忽略了对路径进行邻域搜索,导致路径选取效果不理想。提出基于人工蜂群算法的最短路径智能选取方法,并给出了工业机器人移动过程中的扰动规则;先随机生成若干个可行解作为初始路径;引领蜂对工业机器人移动初始路径进行一次邻域搜索,当引领蜂完成一次完整的领域搜索后将信息传达给跟随蜂,跟随蜂通过精英保留策略进行路径选择,选中一条路径后也会进行一次邻域搜索,保留其中较优的解。实验结果表明,最小代价路径随着蜂群迭代的进行不断自适应调整,获得的工业机器人最短移动路径同时也是全局最小代价路径。

An intelligent selection method of shortest path based on artificial bee colony algorithm of industrial ro- bot is proposed and the disturbance rule is given. Randomly, a certain number of feasible solutions are generated as initial paths. Firstly, the leading bee performed a neighborhood search for initial path of industrial robot. When the leading bee completed a complete neighborhood search, it transmitted information to the following bee. Through the elitism strategy, following bee selected the path, then performed a neighborhood search. Thus, the better solution would be persisted. The results show that the minimum cost path is adaptively adjusted with the bee colony iteration. When the shortest path of industrial robot is obtained, it is also the global minimum cost path.