Adaptive control of manipulators using uncalibrated joint-torque sensing

The application of joint-torque sensory feedback (JTF) in robot control has been proposed in the past that, unlike the model-based controllers, does not require the dynamic model of the robot links. JTF, however, assumes precise measurement of joint torque and accurate friction model of the joints. This paper presents an adaptive JTF control algorithm that does not rely on these assumptions. First, the robot dynamics with JTF is presented in a standard form with a minimum number of parameters, where the inertia matrix appears symmetric and positive definite. Second, an adaptive JTF control law is developed that requires only incorporation of uncalibrated joint-torque signals, i.e., the gains and offsets of multiple sensors are unknown. Also, all physical parameters of the joints including inertia of the rotors, link twist angles, and friction parameters are assumed to be unknown to the controller. The stability analysis of the control system is presented. Experimental results demonstrating the tracking performance of the proposed adaptive JTF controller are presented.