A Neural Network Velocity Estimator for Discrete Position Data

A method of using neural network to estimate the velocity signal of robotic joint from discrete position versus time data is proposed and evaluated. The architecture of the neural net and the training methodology are presented and discussed. Based on computer simulations, comparison of the accuracy of the neural network estimator with two other well established velocity estimation algorithms are made. The neural net approach is able to maintain good performance even in the presence of measurement errors.