Contact Force Control of Robot Polishing System Based on Vision Control Algorithm

Abstract

In this study, an autonomous robotic polishing system leveraging sensor signal processing and control technology is developed. It utilizes a primary-secondary configuration with machine vision and force sensors for intelligent defect detection. The system processes force sensor data to obtain an accurate contact force assessment and performs precise polishing using proportional integral derivative and impedance-based control strategies. It supports remote teaching operator control and autonomous operation of intelligent polishing. Experimental results show that the maximum error between the measured and true values is 0.36 mm. In arc detection, the maximum measurement error between the measured and true values is 1.02mm, and the average error is 0.33mm. This level of accuracy is considered sufficient for the specific applications targeted in this study, such as precision manufacturing, where high accuracy is essential but variability in measurements can be adapted to within a certain range. In actual polishing experiments, the roughness values of the designed industrial robot on pipes and wood were $0.491~\mu $ m and $0.487~\mu $ m, respectively. Most of the polishing of defective locations is completed. Overall, the designed automatic polishing industrial robot is effective and can be applied to polishing operation in industrial production.

Keywords

• Visual control algorithm
• six-dimensional force sensor
• industrial robots
• polishing homework
• measurement error