Kinematic model identification and implementation of redundant robot based on neural networks
冗余度机器人运动模型的神经网络辨识及实现

In order to increase the computational efficiency of neural networks,a new network model named state delay input dynamical recurrent neural network is presented in this study.This new neural network is also applied to the model identification of PowerCube\+\{TM\} modular robot system.The data of joint positions retrieved from the robot and the position of the end-effector measured by the OPTOTRAK 3020 are used as learning sets for neural network.The learning superiority of the new neural network is illustrated.