Load Adaptive Force-free Control for the Direct Teaching of Robots

Comparing with the direct teaching robots with a multi-dimensional force sensor mounted on the end-effector, the robots based on the information from the joint torque sensors, have wider accessible area and are superior in security. But when facing complex tasks with variable loads, the teaching efficiency is constrained, and also affected by the friction force, the gravity and the inertia force on the robot itself.Therefore, a force-free control method is proposed. Firstly, the dynamic model of the flexible-joint manipulator is introduced as the controlled object. The influences of the friction force and the inertia of the motor are analyzed, as well as the gravity of the manipulator in the process of direct teaching. Then, its parameters are identified using QR decomposition and least squares theory to accurately compensate the gravity of the robot. Furthermore, a variable-load adaptive force-free control method is proposed to solve the model parameter change problem caused by replacing the end effector or grasping an object. Finally, experiments are carried out on the self-developed 7-DOF cooperative robot platform. The maximum calculation error of the model is less than 4% of the joint rated torque, after identifying the gravity parameter of the robot itself. In the experiment of single joint force traction, the moment is reduced from about 13 N·m to about 2 N·m by adjusting the force-free control parameters. In robot traction experiment with the variable load, the controller can update the model parameters within 10s. The experiment results show that the control method can help operators to drag the robot easily for an accurate and efficient direct teaching in the case of the load changes.