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Massachusetts Institute of Technology

Policy regularized model predictive control framework for robust legged locomotion

Abstract

dc:description.abstract

A novel Policy Regularized Model Predictive Control (PR-MPC) framework is developed to allow general robust legged locomotion with the MIT Cheetah quadruped robot. The full system is approximated by a simple control model that retains the key nonlinearities characteristic to legged contact dynamics while reducing the complexity of the continuous dynamics. Nominal footstep locations and feedforward forces for controlling the robot's center of mass are designed from simple physics-based heuristics for steady state legged movement. By regularizing the predictive optimization with these policies, we can exploit the known dynamics of the system to bias the controller towards the steady state gait while remaining free to explore the cost space during transient behaviors and disturbances. The nonlinear optimization makes use of direct collocation on the simplified dynamics to pose the problem with a highly sparse structure for fast computation. A generalized approach to the controller design is independent from specific gait pattern and reference policy and allows stabilization of aperiodic locomotion. Simulation results show dynamic capabilities in a variety of gaits including trotting, bounding, and galloping, all without changing the set of algorithm parameters between experiments. Robustness to sensor and input noise, large push disturbances, and unstructured terrain demonstrate the ability of the predictive controller to adapt to uncertainty.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Bledt, Gerardo
Advisor dc:contributor.advisor
  • Sangbae Kim and Russ Tedrake.

Subjects

dc:subject × 2

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/115593
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/115593

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Bledt, Gerardo. Policy regularized model predictive control framework for robust legged locomotion. Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115593