Volume 5 - Issue 4
A new algorithm on compliance control of robots using neural network
Abstract
In this paper a method to implement compliance control of robots is presented. Under the condition of unknowing, the robot's precise model, the robot is approximatively decoupled into a number of independent SISO linear subsystems. An ANN is designed to construct a inverse system and the well-trained ANN inversion is cascaded with the manipulator for decoupling. For the above decoupled position system, a control algorithm based on the target impedance is presented to regulate the impedance of the robot and perform compliance control. Simulation and experimental results show good performance of decoupling and real-time tracking any arbitrary trajectories and validity of this method for compliance control of robots. At the end of the article the elementary rules of adjusting the impedance parameters is summarized.
Paper Details
PaperID: 77949644432
Author's Name: Wang, F.
Volume: Volume 5
Issues: Issue 4
Keywords: Compliance Control, Linear Subsystems, Neural Network, Robot
Year: 2009
Month: August
Pages: 1067 - 1073