A Sensorless Hand Guiding Scheme Based on Model Identification and Control for Industrial Robot

Most industrial robots are not capable of teaching by hand and require path points to be specified by teaching pendants. To enable the teaching of industrial robots by hand without any force sensors, this paper proposes a scheme to minimize the external force estimation error and reduce disturbance in the guiding task by using the virtual mass and virtual friction model. In this case, the maximum velocity and acceleration of the robot end effector shall be limited to ensure safety. Thus, the operator is allowed to guide the robot by hand. The joint torque is obtained from the motor current. The inertial force and friction of the links and driving systems are analyzed. The nonlinear dynamic model of the industrial robot is built and its parameters are calibrated by a nonlinear method. The force estimation is referenced to set the virtual friction and to design the force-following controller. Hence the end effector can follow the direction of external force compliantly and suppress jitters. Finally, several experiments on a six degrees of freedom industrial robot demonstrate the validity of the proposed control scheme.