Whole-Body Nonlinear Model Predictive Control Through Contacts for Quadrupeds

By Michael Neunert, M. Stäuble, Markus Giftthaler, C. D. Bellicoso, Jan Carius, Christian Gehring, Marco Hutter, Jonas Buchli. IEEE Robotics and Automation Letters, 2017

303 citations recorded by the source corpus.

In this letter, we present a whole-body nonlinear model predictive control approach for rigid body systems subject to contacts. We use a full-dynamic system model which also includes explicit contact dynamics. Therefore, contact locations, sequences, and timings are not prespecified but optimized by the solver. Yet, using numerical and software engineering allows for running the nonlinear Optimal Control solver at rates up to 190 Hz on a quadruped for a time horizon of half a second. This outperforms the state-of-the-art by at least one order of magnitude. Hardware experiments in the form of periodic and nonperiodic tasks are applied to two quadrupeds with different actuation systems. The obtained results underline the performance, transferability, and robustness of the approach.

Subfields: Biomedical Engineering, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/772e90438a12f9abbdb364ea18775d7890d179aa

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Citations in the corpus

Data Efficient Reinforcement Learning for Legged Robots (2019, methodology): “With handcrafted models, a number of efﬁcient planning algorithms have been tested for robot loco-motion [19, 20, 21].”
Highly Dynamic Quadruped Locomotion via Whole-Body Impulse Control and Model Predictive Control (2019, unknown): “This limited time horizon issue has been addressed in [10], [11] which developed an MPC formulation using full-body dynamics.”
Crocoddyl: An Efficient and Versatile Framework for Multi-Contact Optimal Control (2019, background): “Recent work on optimal control has shown that nonlinear Model Predictive Control (MPC) is plausible for controlling legged robots in real-time [15], [16], [17].”
Dynamic Locomotion in the MIT Cheetah 3 Through Convex Model-Predictive Control (2018, background): “…at the Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. email: dicarloj@mit.edu , pwensing@nd.edu , benkatz@mit.edu , gbledt@mit.edu , sangbae@mit.edu recently, the experimental results in [12] show that whole-body nonlinear MPC can be used to stabilize trotting and jumping.”