【摘要】 针对未知环境下的机器人路径规划问题 ,提出了一种基于自学习可见图与局部最优的路径规划算法 .在这种算法中 ,采用自学习可见图来表示环境 ,并在路径规划的过程中逐步建立自学习可见图 .在避障上设计一个局部最优算法并提出了一种局部路径规划算法 .实验表明 :该方法规划速度快 ,并且能规划出局部最优的路径 ,满足未知环境下机器人路径规划的要求 .更多还原

【Abstract】 A new path planning method of mobile robot in unkown enviroment using self-learn visual graph is proposed. In this paper, a presentation named by self-learn visual graph(SLVG) is used to represent unkown environment, the SLVG is empty at first, when the path planning is conduct, the SLVG is built partly, when the path planning is finished, the SLVG is built completely. On the base of SLVG, a local optimal obstacle avoidance algorithm and a local optimal path planning algorithm are also present in the paper. Experimental results using simulation demonstrate that the method is fast and can produce a local optimal path for mobile robot in unknown environment.更多还原