基于蚁群算法深海采矿机器人工作路径规划

针对深海采矿机器人路径规划问题,提出一种适合于采矿作业的改进蚁群算法。该算法利用位图法建立环境模型,依据构型空间的思想将路径规划问题简化为质点运动问题;利用改进的蚁群算法对问题进行描述,蚁群搜索中采用邻居搜索原则和中线偏移策略。最后通过仿真实验表明,该算法精度高,在海底环境中,能够完成机器人采矿作业的要求。

Path planning for deep sea mining robot based on ant colony algorithm

An improved ant colony algorithm(ACA) is proposed in order to resolve the path planning problem for seep sea mining robot.The environmental model is established with bitmap method,and robot movement is simplified into particle movement by using framework method.Furthermore,neighbor search and movement to midline strategies are added to ACA.Results of simulation experiments demonstrate that this method can satisfy the demand of robot mining work in deep sea.