Model-Based On-line Estimation of Time-Varying Nonlinear Joint Stiffness on an e-Series Universal Robots Manipulator

Abstract

Flexibility commonly exists in the joints of many industrial robots due to the elasticity of the lightweight strain-wave type transmissions being used. This leads to a dynamic time-varying displacement between the position of the drive actuator and that of the driven link. Furthermore, the joint flexibility changes with time due to the material slowly being worn off at the gear meshing. Knowing the stiffness of the robot joints is of great value, e.g. in the design of new model-based feedforward and feedback controllers, and for predictive maintenance in the case of gearing unit failure. In this paper, we address on-line estimation of robot joint stiffness using a recursive least squares strategy based on a parametric model taking into account the elastic torques’ nonlinear dependency on transmission deformation. Robustness is achieved in the presence of measurement noise and in poor excitation conditions. The method can be easily extended to general classes of serial-link multi-degree-of-freedom robots. The estimation technique uses only feedback signals that are readily available on Universal Robots’ e-Series manipulators. Experiments on the new UR5e manipulator demonstrate the effectiveness of the proposed method.