Force control of a grinding robotic manipulator with floating base via model predictive control

Abstract

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. In this paper, a grinding robot for a large area and an applied control method are described. A robot consisting of a grinding module and a manipulator 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 optimal impedance control applied with model-based prediction is proposed as a control technique for grinding robots. Lab tests were conducted to verify the performance of the proposed control method. Impedance control with model prediction-based optimization confirmed faster force-following performance than conventional impedance control, and showed robust control performance even in the presence of grinding disturbance. As a result, proposed optimal impedance force control via model-based prediction shows improved force tracking performance over previous impedance control, and is presented as one of the appropriate control methods for grinding robots targeting large areas.