The Surprising Effectiveness of Linear Models for Whole-Body Model-Predictive Control

Fuente: arXiv
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Main Authors: Bishop, Arun L., Alvarez-Padilla, Juan, Schoedel, Sam, Sow, Ibrahima Sory, Chandrachud, Juee, Sharma, Sheitej, Kraus, Will, Park, Beomyeong, Griffin, Robert J., Dolan, John M., Manchester, Zachary
Format: Preprint
Published: 2025
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author Bishop, Arun L.
Alvarez-Padilla, Juan
Schoedel, Sam
Sow, Ibrahima Sory
Chandrachud, Juee
Sharma, Sheitej
Kraus, Will
Park, Beomyeong
Griffin, Robert J.
Dolan, John M.
Manchester, Zachary
author_facet Bishop, Arun L.
Alvarez-Padilla, Juan
Schoedel, Sam
Sow, Ibrahima Sory
Chandrachud, Juee
Sharma, Sheitej
Kraus, Will
Park, Beomyeong
Griffin, Robert J.
Dolan, John M.
Manchester, Zachary
contents When do locomotion controllers require reasoning about nonlinearities? In this work, we show that a whole-body model-predictive controller using a simple linear time-invariant approximation of the whole-body dynamics is able to execute basic locomotion tasks on complex legged robots. The formulation requires no online nonlinear dynamics evaluations or matrix inversions. We demonstrate walking, disturbance rejection, and even navigation to a goal position without a separate footstep planner on a quadrupedal robot. In addition, we demonstrate dynamic walking on a hydraulic humanoid, a robot with significant limb inertia, complex actuator dynamics, and large sim-to-real gap.
format Preprint
id arxiv_https___arxiv_org_abs_2509_17884
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Surprising Effectiveness of Linear Models for Whole-Body Model-Predictive Control
Bishop, Arun L.
Alvarez-Padilla, Juan
Schoedel, Sam
Sow, Ibrahima Sory
Chandrachud, Juee
Sharma, Sheitej
Kraus, Will
Park, Beomyeong
Griffin, Robert J.
Dolan, John M.
Manchester, Zachary
Robotics
When do locomotion controllers require reasoning about nonlinearities? In this work, we show that a whole-body model-predictive controller using a simple linear time-invariant approximation of the whole-body dynamics is able to execute basic locomotion tasks on complex legged robots. The formulation requires no online nonlinear dynamics evaluations or matrix inversions. We demonstrate walking, disturbance rejection, and even navigation to a goal position without a separate footstep planner on a quadrupedal robot. In addition, we demonstrate dynamic walking on a hydraulic humanoid, a robot with significant limb inertia, complex actuator dynamics, and large sim-to-real gap.
title The Surprising Effectiveness of Linear Models for Whole-Body Model-Predictive Control
topic Robotics
url https://arxiv.org/abs/2509.17884