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Hierarchical planning and control for complex motor tasks

Published: 07 August 2015 Publication History

Abstract

We present a planning and control framework that enables physically simulated characters to perform various types of motor tasks. To create physically-valid motion plans, our method uses a hierarchical set of simplified models. Computational resources are therefore focused where they matter most: motion plans for the immediate future are generated using higher-fidelity models, while coarser models are used to create motion plans with longer time horizons. Our framework can be used for different types of motor skills, including ones where the actions of the arms and legs must be precisely coordinated. We demonstrate controllers for tasks such as getting up from a chair, crawling onto a raised platform, or using a handrail while climbing stairs. All of the motions are simulated using a black-box physics engine from high level user commands, without requiring any motion capture data.

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Cited By

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  • (2022)Offline motion libraries and online MPC for advanced mobility skillsThe International Journal of Robotics Research10.1177/0278364922110247341:9-10(903-924)Online publication date: 7-Jun-2022
  • (2020)Fast and flexible multilegged locomotion using learned centroidal dynamicsACM Transactions on Graphics10.1145/3386569.339243239:4(46:1-46:17)Online publication date: 12-Aug-2020
  • (2018)Real-time locomotion with character-fluid interactionsProceedings of the 11th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3274247.3274515(1-8)Online publication date: 8-Nov-2018
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    cover image ACM Conferences
    SCA '15: Proceedings of the 14th ACM SIGGRAPH / Eurographics Symposium on Computer Animation
    August 2015
    193 pages
    ISBN:9781450334969
    DOI:10.1145/2786784
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 07 August 2015

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    Author Tags

    1. control
    2. motion planning
    3. physics-based character animation

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    Cited By

    View all
    • (2022)Offline motion libraries and online MPC for advanced mobility skillsThe International Journal of Robotics Research10.1177/0278364922110247341:9-10(903-924)Online publication date: 7-Jun-2022
    • (2020)Fast and flexible multilegged locomotion using learned centroidal dynamicsACM Transactions on Graphics10.1145/3386569.339243239:4(46:1-46:17)Online publication date: 12-Aug-2020
    • (2018)Real-time locomotion with character-fluid interactionsProceedings of the 11th ACM SIGGRAPH Conference on Motion, Interaction and Games10.1145/3274247.3274515(1-8)Online publication date: 8-Nov-2018
    • (2018)Fast behavioral locomotion with layered navigation meshesProceedings of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games10.1145/3190834.3190841(1-6)Online publication date: 15-May-2018
    • (2018)Real‐time Locomotion Controller using an Inverted‐Pendulum‐based Abstract ModelComputer Graphics Forum10.1111/cgf.1336137:2(287-296)Online publication date: 22-May-2018
    • (2018)A Comparative Analysis of Contact Models in Trajectory Optimization for Manipulation*2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS.2018.8594284(1-9)Online publication date: Oct-2018
    • (2017)Trajectory Optimization Through Contacts and Automatic Gait Discovery for QuadrupedsIEEE Robotics and Automation Letters10.1109/LRA.2017.26656852:3(1502-1509)Online publication date: Jul-2017
    • (2016)Full-body behavioral path planning in cluttered environmentsProceedings of the 9th International Conference on Motion in Games10.1145/2994258.2994281(107-112)Online publication date: 10-Oct-2016
    • (2016)Efficient whole-body trajectory optimization using contact constraint relaxation2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)10.1109/HUMANOIDS.2016.7803252(43-48)Online publication date: Nov-2016

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