Motion Compensation of Omnidirectional Wheel Robot Using Neural Networks

This paper describes a method to compensate the omnidirectional robot´s motion control. Due to the variation of individual mechanical characteristics, there always have some errors between the given command and the robot´s execution. The paper explains how we cope with the execution errors by two neural networks modeling the rotation and translation individually. And we have successfully field-tests the compensation method at several RoboCup events with our ZjuNlict team. The result shows that the compensation can significantly improve the accuracy of robotic play