基于BP神经网络的移动机器人路径规划

Path Planning for Mobile Robot Based on BP Neural Network Algorithm

对BP神经网络算法进行了改进,克服了直接使用神经网络算法进行路径规划的不足之处。仿真表明,设计了附加动量项的BP神经网络,能有效地提高算法的收敛速度。最后在MAT-LAB中给出了在有静止和运动障碍物的动态环境中路径规划仿真结果,结果表明此方法是可行的。

Improves the BP neural network algorithm, so the shortage of path - planning with the BP neural network algorithm is overcomed . The simulation results indicate that on the bases of accessional momentum method can efficiently improve this algorithm in convergence speed. At last, mobile robot dynamic path planning simulation is carried out in the environment with immobile and mobile obstacle, the simulation result indicates that the method is feasible.