煤炭勘探及救援机器人最优路径规划研究

摘要

为了解决三维环境中的煤炭勘探及救援机器人路径规划问题,提出了一种基于改进蚁群算法的煤炭勘探及救援机器人最优路径规划方法.利用栅格法创建了三维空间环境模型,建立了煤炭勘探及救援机器人的路径规划目标函数;通过引入新的启发函数因子、节点随机选择机制、局部更新和全局更新相结合的策略分别对算法的节点转移概率设计、节点选择策略和信息素更新策略进行了优化改进.Matlab仿真结果表明,在三维空间环境模型中,传统蚁群算法和改进蚁群算法均能为煤炭勘探及救援机器人搜索出一条最优路径;在不同任务要求下,改进蚁群算法能有效缩短搜索路径长度和降低路径搜索时间,且具有较强的决策能力和较好的收敛性能.%In order to solve path planning problem of coal exploration and rescue robots in threedimentional environment,an optimal path planning method for coal exploration and rescue robot based on improved ant colony algorithm was proposed.Three-dimensional space environment model is established by using grid method,and path planning objective function of coal exploration and rescue robot is established.Node transition probability design,node selection strategy and pheromone update strategy are optimized and improved by introducing new heuristic function factor,random selection mechanism of node and combining strategy of local updating and global updating.Matlab simulation results show that both the traditional ant colony algorithm and the improved ant colony algorithm can find an optimal path for the coal exploration and rescue robot in the three-dimensional environment model.Under different task requirements,the improved ant colony algorithm can effectively shorten the length of search path and reduce time of path search,and has strong decision-making ability and good convergence performance.