Adaptive lead-through teaching control for spray-painting robot with closed control system


 Industrial robots are widely used in the painting industry, such as automobile manufacturing and solid wood furniture industry. An important problem is how to improve the efficiency of robot programming, especially in the current furniture industry with multiple products, small batches and increasingly high demand for customization. In this work, we propose an outer loop adaptive control scheme, which allow users to realize the practical application of the zero-moment lead-through teaching method based on dynamic model without opening the inner torque control interface of robots. In order to accurately estimate the influence of joint friction, a friction model is established based on static, Coulomb and viscous friction characteristics, and the Sigmoid function is used to represent the transition between motion states. An identification method is used to quickly identify the dynamic parameters of the robot. The joint position/speed command of the robot’s inner joint servo loop is dynamically generated based on the user-designed adaptive control law. In addition, the zero-moment lead-through teaching scheme based on the dynamic model is applied to a spray-painting robot with closed control system. In order to verify our method, CMA GR630ST is used to conduct experiments. We identified the parameters of the dynamic model and carried out the zero-moment lead-through teaching experiment to track the target trajectory. The results show that the proposed method can realize the application of modern control methods in industrial robot with closed control systems, and achieve a preliminary exploration to improve the application scenarios of spray-painting robots.