research-article

DOC: Differentiable Optimal Control for Retargeting Motions onto Legged Robots

Authors:

Farbod Farshidian,

Christian Schumacher,

Moritz BächerAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 42, Issue 4

Article No.: 96, Pages 1 - 14

https://doi.org/10.1145/3592454

Published: 26 July 2023 Publication History

Abstract

Legged robots are designed to perform highly dynamic motions. However, it remains challenging for users to retarget expressive motions onto these complex systems. In this paper, we present a Differentiable Optimal Control (DOC) framework that facilitates the transfer of rich motions from either animals or animations onto these robots. Interfacing with either motion capture or animation data, we formulate retargeting objectives whose parameters make them agnostic to differences in proportions and numbers of degrees of freedom between input and robot. Optimizing these parameters over the manifold spanned by optimal state and control trajectories, we minimize the retargeting error. We demonstrate the utility and efficacy of our modeling by applying DOC to a Model-Predictive Control (MPC) formulation, showing retargeting results for a family of robots of varying proportions and mass distribution. With a hardware deployment, we further show that the retargeted motions are physically feasible, while MPC ensures that the robots retain their capability to react to unexpected disturbances.

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https://dl.acm.org/doi/10.1111/cgf.15175
Zhang QCui PYan DSun JDuan YHan GZhao WZhang WGuo YZhang AXu R(2024)Whole-body Humanoid Robot Locomotion with Human Reference2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10801451(11225-11231)Online publication date: 14-Oct-2024
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Index Terms

DOC: Differentiable Optimal Control for Retargeting Motions onto Legged Robots
1. Computing methodologies
  1. Computer graphics
    1. Animation
      1. Physical simulation

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cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 42, Issue 4

August 2023

1912 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/3609020

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Published: 26 July 2023

Published in TOG Volume 42, Issue 4

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https://dl.acm.org/doi/10.1111/cgf.15175
Zhang QCui PYan DSun JDuan YHan GZhao WZhang WGuo YZhang AXu R(2024)Whole-body Humanoid Robot Locomotion with Human Reference2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10801451(11225-11231)Online publication date: 14-Oct-2024
https://doi.org/10.1109/IROS58592.2024.10801451
Tang AHiraoka THiraoka NShi FKawaharazuka KKojima KOkada KInaba M(2024)HumanMimic: Learning Natural Locomotion and Transitions for Humanoid Robot via Wasserstein Adversarial Imitation2024 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA57147.2024.10610449(13107-13114)Online publication date: 13-May-2024
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Alemayoh TLee JOkamoto S(2023)A Deep Learning Approach for Biped Robot Locomotion Interface Using a Single Inertial SensorSensors10.3390/s2324984123:24(9841)Online publication date: 15-Dec-2023
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