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arXiv · 1902.10415

Whole-Body MPC for a Dynamically Stable Mobile Manipulator

Maria Vittoria Minniti·Farbod Farshidian·Ruben Grandia·Marco Hutter
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Abstract

Autonomous mobile manipulation offers a dual advantage of mobility provided by a mobile platform and dexterity afforded by the manipulator. In this paper, 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.

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Maria Vittoria Minniti, Farbod Farshidian, Ruben Grandia, Marco Hutter. 2019-07-15. Whole-Body MPC for a Dynamically Stable Mobile Manipulator. https://doi.org/10.1109/lra.2019.2927955

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