Whole-Body MPC for a Dynamically Stable Mobile Manipulator
Maria Vittoria Minniti, Farbod Farshidian, Ruben Grandia, Marco Hutter
Abstract
Autonomous mobile manipulation offers a dual advantage of mobility provided by a mobile platform and dexterity afforded by the manipulator. In this letter, we present a whole-body optimal control framework to jointly solve the problems of manipulation, balancing and interaction, as one optimization problem for an inherently unstable robot. The optimization is performed using a model predictive control (MPC) approach; the optimal control problem is transcribed at the end-effector space, treating the position and orientation tasks in the MPC planner, and skillfully planning for end-effector contact forces. The proposed formulation evaluates how the control decisions aimed at end-effector tracking and environment interaction will affect the balance of the system in the future. We showcase the advantages of the proposed MPC approach on the example of a ball-balancing robot with a robotic manipulator and validate our controller in hardware experiments for tasks such as end-effector pose tracking and door opening.
BibTeX
@inproceedings{ral2019_wholebodympcfora,
title = {Whole-Body MPC for a Dynamically Stable Mobile Manipulator},
author = {Maria Vittoria Minniti and Farbod Farshidian and Ruben Grandia and Marco Hutter},
booktitle = {RA-L 2019},
year = {2019}
}