Abstract
The standard robot identification method is based on the use of the inverse dynamic model (IDM) and the application of Least Squares (LS) estimation while the robot is tracking trajectories. Although this approach has been successfully applied to several industrial robots, the standard friction model is assumed to be linear. In this paper, a two-step LS approach is proposed that corrects this limitation. In the first step, State-Dependent-Parameter (SDP) estimation is combined with the IDM to identify the nature of the friction effect. In a second step, the standard LS method is performed in order to obtain the estimates of the inertia and gravity parameters. The experimental results obtained on the 6 degrees-of-freedom TX40 robot show the effectiveness of this new approach.
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