Performance improvement of implicit integral robot force control through constraint-based optimization
Matteo Parigi Polverini, Roberto Rossi, Giacomo Morandi, Luca Bascetta, A. M. Zanchettin, Paolo Rocco
Abstract
Classical control approaches to robot force control have been extensively addressed by research in the last decades and are now considered a paradigm when dealing with force control for industrial robots. With this respect, the present paper exploits the capability of state-of-the-art Quadratic Programming (QP) solvers to specify a simple and intuitive constraint-based optimization strategy aiming at improving closed-loop performance of a classical force controller, such as the implicit force control with pure integral action for a position-controlled manipulator in contact with a compliant environment. The effectiveness of the proposed control strategy is experimentally validated on an industrial robot equipped with a force sensor.
BibTeX
@inproceedings{iros2016_performanceimpro,
title = {Performance improvement of implicit integral robot force control through constraint-based optimization},
author = {Matteo Parigi Polverini and Roberto Rossi and Giacomo Morandi and Luca Bascetta and A. M. Zanchettin and Paolo Rocco},
booktitle = {IROS 2016},
year = {2016}
}