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基于神经网络的移动机器人路径规划

Keywords: 路径规划,神经网络,扩展卡尔曼滤波器

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Abstract:

针对移动机器人在部分环境信息已知情况下的路径规划问题,运用神经网络动态路径最优算法,研究了基于传感器信息的在线路径规划方法.基于扩展卡尔曼滤波的定位方法融合了多个与机器人状态及环境相关的信息,提高了定位精度.首先建立动态的工作空间信息,基于神经网络的路径规划算法完成机器人的路径规划,根据路径点集运动趋向来调节小车移动,完成了导航的任务.对算法的性能和效率进行了分析,实验表明该方法在障碍物的信息未知的情况下,执行速度快.

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