蚁群算法在移动机器人路径规划中的仿真研究

摘要

研究移动机器人路径规划问题.移动机器人路径规划是一个多目标优化问题,由于避障定位要求,传统机器人路径规划优化方法存在算法复杂、搜索空间大和效率低等难题,难以获得最优解.为了提高机器路径规划的效率和定位准确性,提出了一种蚁群算法的移动机器人路径规划方法.蚁群算法的路径规划方法首先采用栅格法对机器人工作环境进行建模,然后将机器人出发点作为蚁巢位置,路径规划最终目标点作为蚁群食物源,通过蚂蚁间相互协作找到-条避开障碍物的最优机器人移动路径.仿真实验结果证明,蚁群算法的路径规划方法提高了机器人路径规划的效率,能在最短时间找到机器人路径规划最优解,且能安全避开障碍物,为优化设计提供了依据.%Ant colony algorithm performs better than traditional optimal algorithms in many fields. In order to improve the efficiency of mobile robot path planning, a mobile robot optimal path planning method is proposed based on ant colony algorithm. This method firstly build up the environment modeling by grid, the starting point is used as ant nest while the ultimate goal point position as a food source. The optimal path is found by ants cooperation. Back strategy is used to prevent robot path search fall into deadlock state. Experimental results show that this algorithm can improve the efficiency of the robot path planning, get the optimal robot path and avoid the obstacle safety.