基于融合边界信息的机器人路径选择方法研究

A Route Selection Method Based on fusion information of obstacle boundary

研究了机器人融合多元视觉边界信息检测障碍并选择可行路径实现导航的方法。针对检测到的视觉环境信息,研究了多元边界表示与提取算法,通过融合处理得到了实际环境中前进方向上的径向障碍分布(ROP),研究了相关的路径规划算法。对如何提高边界提取算法效率以及在机器人尺寸和实时速度约束条件下的规划等问题提出改进算法,实现了非结构化环境下机器人的局部导航控制。实际机器人在不同环境下的实验,验证了所研究算法的有效性。

A method based on multiple visual-edges information fusion is proposed for obstacle detecting and route selection. Based on the visual information of the environment, the muhi-edge exacting algorithm is presented to obtain the Radial Obstacle Profile. According to the ROP, an advanced route selection algorithm considering the robot size and real-time velocity to navigate robot in unstructured environment is proposed. The efficiency and feasibility of the method has been proved by the physical robot experiment in different environments.