Consistent dynamic model identification of the Stäubli RX-160 industrial robot using convex optimization method

Abstract

Dynamic models of robot manipulators with standard dynamic parameters are required for simulations, model-based controller design and external force estimation. The aim of this work is to identify the complete dynamic model of the 6-axis Staubli RX-160 industrial robot. A convex optimization-based method is used for parameter identification. Consistent model parameters are obtained as the result of the optimization procedure subject to physical constraints. Low-speed behavior of the robot being dominated by joint friction, the dynamic model includes an algebraic friction model consisting of the Coulomb and viscous friction components along with the Stribeck effect. The coupled mechanical structure of the 5th and 6th joints, and elasticity due to the presence of balancing springs are also represented in the proposed dynamic model. The ordinary least square error method is used for the performance evaluation of the convex optimization-based method. Estimated parameters from both methods are experimentally verified over identification and test trajectories. The identified model is finally used as a basis in the estimation of external forces acting on the robot’s end-effector. The proposed sensor-less model-based approach for the estimation of external forces constitutes an alternative mean of experimental validation. Comparison of computed external forces with measured ones by an F/T transducer shows that the dynamic model obtained with the proposed method provides an accurate estimation.