Abstract: An online path planning method is presented for unknown environment－Real－time Planning－Choosing algorithm.The BUG algorithm and the two－level strategies of path choice presented following combine to decide robot’s action.In the method two－level strategies of path choice simulates the human’s thinking mode in order to decide which direction of obstacle robot should follow.The RPC algorithm can reduce the blindness of robot in avoiding obstacles and path redundancy,also the robot can adapt to more complex environment.At last,simulation result indicates the feasibility of the algorithm．

摘要： 提出一种适合存在多种类型障碍的完全未知环境的机器人路径规划方法：RPC算法（全称为实时规划－选择算法）。即将BUG规划算法与所提出的两级路径选择策略相结合实时决策机器人的行为。其中两级路径选择策略模拟人类探索路径的思维模式实时决定机器人绕行障碍的方向,能够减小机器人避障中的盲目性和降低路径冗余度。此算法提高了机器人在未知环境中的智能性,增强了对较复杂环境的适应性。仿真实验表明了该算法的可行性。