Force Control of a Grinding Robotic Manipulator With Floating Base Via Model Prediction Optimization Control

Abstract

In this article, a grinding robot for large area and an impedance-based force control method applied to the robot are described. With the development of science and technology, the demand for various industrial robots increased, and among them, the demand and importance of grinding robots that require high risk and precision increased. In particular, research on grinding robots targeting large areas has not been conducted relatively, and accordingly, the design and control mechanism of robots specialized in large areas was needed. A robot consisting of a manipulator and a grinding module with a 2-DOF parallel structure is proposed as the design of a new grinding robot. The control method is based on impedance force control mainly used in existing grinding robots, but to overcome the limitations of using only impedance control, the impedance control via model-based prediction optimization (MPO) is proposed as a control technique for grinding robots. Experiments were conducted to verify the force tracking ability of the proposed control, resulting in a 28.1% improvement in settling time for the desired force. Even for disturbance, more improved recovery performance than conventional controllers has been verified. As a result, proposed impedance force control via MPO shows improved force tracking performance over conventional impedance control, and is presented as one of the appropriate control methods for grinding robots targeting large areas.