Whole-Body MPC for a Dynamically Stable Mobile Manipulator

• 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
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2019.2927955

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.