Whole-Body MPC for a Dynamically Stable Mobile Manipulator

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...

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Bibliographic Details
Published in:IEEE robotics and automation letters 2019-10, Vol.4 (4), p.3687-3694
Main Authors: Minniti, Maria Vittoria, Farshidian, Farbod, Grandia, Ruben, Hutter, Marco
Format: Article
Language:English
Subjects:
Balancing
Contact force
End effectors
Manipulator dynamics
Manipulators
Mobile manipulation
Optimal control
Optimization
optimization and optimal control
Planning
Predictive control
Robot arms
Robot kinematics
Task analysis
Tracking
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Summary: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.
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2019.2927955