COMBINING INTERNAL AND EXTERNAL ROBOT MODELS FOR IMPROVED MODEL PARAMETER ESTIMATION

Experimental robot identification techniques can principally be divided into two categories, based on the type of models they use : internal or external. Internal models relate the joint torques or forces and the motion of the robot; external models relate the reaction forces and torques on the bedplate and the motion data. This paper describes how internal and external robot models can be combined into one identifiable minimal model. This model allows to combine joint torque/force and reaction torque/force measurements in one parameter estimation scheme. This combined model estimation will yield more accurate parameter estimates, and consequently better actuator torque predictions, which is shown by means of a simulated experiment on an industrial robot (KUKA IR 361). This increased accuracy is quite interesting in view of using advanced control algorithms such as computed torque control.