中文摘要：

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.

英文摘要：

To complete non-collision movement according to the environment information when it is in an unknown, complex,dynamic change condition, a reliable navigation of a mobile robot is demonstrated. The data about the states of the robot is fused using the framework of extended Kalman filter to localize a mobile robot more accurately. After the information of the dynamic workspace is constructed, an algorithm based on neural network is used. The navigation is implemented by adjusting the motion according to the tendency of the points set. Parameter optimization of the algorithm is investigated, and experiments and the simulations reveal that this method performs effectively without the information of the obstacle.