Path planning of robot based on neural network and PSO

A new method of neural network and particle swarm algorithm based mobile robot path planning was proposed. With combination of the advantages of wavelet network and RBF network, a four layers neural network was designed. In conventional method, many hidden cells should design for every obstacle according to information of blocks, and the scale of network was very large with many obstacles. So PSO was used to train the parameters of neural network with its character of quick optimization to make the robot respond quickly to the dynamic environment. At last, the effectiveness of the method was proved by simulation experiments of mobile robotic in dynamic and static environments.