Global Vision-Based Impedance Control for Robotic Wall Polishing
Yang Zhou, Xiang Li, Linzhu Yue, Linhai Gui, Guangli Sun, Xin Jiang, Yun-Hui Liu
Abstract
Wall polishing is a typical and essential procedure in the interior renovation. However, such works are mainly carried out by humans, which have the disadvantages of low efficiency, inconsistent quality, and issues of safety and health. A new vision-based impedance controller is proposed for polishing robots to automate the labor-intensive works. The desired impedance model is specified as the control objective to regulate the dynamic relationship between the interaction force and the motion of the robot end effector, where the motion is measured with the vision feedback. The use of the vision feedback guarantees the performance of the robot from two aspect. First, the vision feedback from the high-resolution camera ensures the accuracy of measurement of the robot end effector and hence guarantees the quality of polishing. Second, the concept of image moment is introduced such that the image Jacobian matrix is non-singular in a global sense, which guarantees the large working range of the robot. The dynamic stability of the closed-loop system is rigorously proved with Lyapunov methods, and experimental results are presented to illustrate the performance of the proposed controller.
BibTeX
@inproceedings{iros2019_globalvisionbase,
title = {Global Vision-Based Impedance Control for Robotic Wall Polishing},
author = {Yang Zhou and Xiang Li and Linzhu Yue and Linhai Gui and Guangli Sun and Xin Jiang and Yun-Hui Liu},
booktitle = {IROS 2019},
year = {2019}
}