Research on the dynamic modeling based on genetic wavelet neural network for the robot wrist force sensor

Abstract

A kind of new dynamic modeling method is presented based on improved genetic algorithm (IGA) and wavelet neural networks (WNN) and the algorithm is applied to a new type of robot wrist force sensor. The dynamic model of the wrist force sensor is set up according to data of the dynamic calibration, where the structure and parameters of wavelet neural networks of the dynamic model are optimized by genetic algorithm. The results show that the proposed method can overcome the shortcoming of easy convergence to the local minimum points of BP algorithm, and the network complexity, the convergence and the generalization ability are well compromised and the speed and precision of modeling are increased.