By exploiting an a priori estimate of the dynamic model of a manipulator, it is possible to command joint torques which ideally realize a Feedback Linearization (FL) controller. The exact cancellation may nevertheless not be achieved due to model uncertainties and possible errors in the estimation of the dynamic coefficients. In this work, an online learning scheme for control based on FL is presented. By reading joint positions and joint velocities information only (without the use of any torque measurement), we are able to learn those model uncertain- ties and thus achieve perfect FL control. Simulations results on the popular KUKA LWR iiwa robot are reported to show the quality of the proposed approach.
2019, Proceedings of 2019 Conference on Robot Learning, Pages -
An online learning procedure for feedback linearization control without torque measurements (04b Atto di convegno in volume)
CAPOTONDI MARCO, TURRISI GIULIO, GAZ CLAUDIO ROBERTO, MODUGNO VALERIO, ORIOLO Giuseppe, DE LUCA Alessandro
Gruppo di ricerca: Robotics