摘要:
研究了全局静态环境未知时机器人的路径规划问题,提出了一种新颖的滚动规划蚂蚁算法.该方法将目标点映射到机器人视野域附近,再由两组蚂蚁采用最近邻居搜索策略相互协作完成机器人局部最优路径的搜索,机器人每前进一步,都由蚂蚁对局部路径重新搜索,因此,机器人前进路径不断动态修改,从而能使机器人沿一条全局优化的路径到达终点.仿真实验结果表明,即使在障碍物非常复杂的地理环境,用本算法也能迅速规划出一条优化路径,且能安全避碰,效果十分令人满意.
Abstract:
The problem of path planning of mobile robot in an environment where the global information is unknown is studied, and a novel ant algorithm based on rolling planning is proposed. First, the object node is mapped to a node nearby the external of eyeshot of the mobile robot, then two groups of ants cooperatively execute a search for the local optimal path for the robot using the nearest-neighbor searching strategy. The ants will execute a local search again once the robot goes forward. So, the path for the robot is altered dynamically, which will make the robot move on a globally optimal path to the ending node. Simulation results indicate that the optimal path which the robot moves on can reach to the end safely and can be rapidly obtained even in complicated geographical environments, the effect being very satisfactory.
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