Disney Research


In this paper, we examine joint torque tracking as well as estimation of external torques for the KUKA Lightweight Robot (LBR) IIWA. To support physical human-robot interaction tasks, we need smooth estimation that allows detection of delicate external events and good control to hide inertial forces. Unfortunately, a transmission nonlinearity in the motor to joint gearing injects vibrations and limits the performance of the built-in torque controller and observer. We confirm the nonlinearity to be a spatially periodic deflection between the motor and joint. Identification of this behavior allows us to generate more accurate joint position measurements. We also design a matching spatial filter to remove the vibrations from joint torque measurements. Experiments on an LBR IIWA show that compensating for the nonlinearity provides smoother external torque estimates and improves the torque tracking performance. Furthermore, we are able to increase the gain margin more than three-fold over the built-in controller.

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