IROS 2017Poster

Robust set invariance for implicit robot force control in presence of contact model uncertainty

作者: Matteo Parigi Polverini, Davide Nicolis, Andrea Maria Zanchettin, Paolo Rocco

摘要

The present paper exploits set invariance theory to address the problem of robot implicit force control in presence of stiffness uncertainty in the interaction model. A numerical approach is introduced to compute the invariance function for constraints with arbitrary relative degree. The method is then applied to robot force control, enhancing force regulation performance, in terms of steady state error and convergence speed, despite model mismatch and measurement noise. Its effectiveness is experimentally validated and compared to previous results of set invariance control on a hybrid force/position task performed with a 6 degrees of freedom industrial robot equipped with a force/torque sensor.

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