基于模糊神经网络的煤矿救援机器人路径规划研究

Research on Path Planning for Mine Rescue Robot Based on Fuzzy Neural Network

针对煤矿灾后的非结构化环境,提出了一种基于模糊神经网络的救援机器人全局路径规划算法,同时采用BP反向传播学习算法对网络进行训练,有效提高了在线精度和神经网络的学习速度。Matlab仿真证明,该算法效率高、收敛速度快,能实现救援机器人连续、快速地避开静态或动态障碍物。

Aiming at the unstructured environment after coal mine disaster,a global path planning algorithm for rescue robot based on fuzzy neural network is proposed.The BP back propagation learning algorithm is used to train the network,which effectively improves the online precision of rules and the learning speed of the network.Matlab simulation proves that the algorithm has high efficiency and fast convergence speed,which can realize the continuous and rapid avoidance of static or dynamic obstacles by rescue robots.