Unified Push Recovery Fundamentals: Inspiration from Human Study

Christopher McGreavy, Kai Yuan, Daniel Gordon, Kang Tan, Wouter J. Wolfslag, Sethu Vijayakumar, Zhibin Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Currently for balance recovery, humans outperform humanoid robots that used hand-designed controllers. This study aims to close this gap by finding control principles which are shared across all recovery strategies. We do this by formulating experiments to test human strategies and quantify criteria for identifying strategies. A minimum jerk control principle is shown to accurately recreate human CoM recovery trajectories. Using this principle, we formulate a Model-Predictive Control (MPC) for the use in floating base systems (eg legged robots). The feasibility of generated motions from the MPC for implementation on the real robot is then validated using an Inverted Pendulum Model. Finally, we demonstrate improved capability over humans by tuning the parameters for time-optimal recovery performance.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Robotics and Automation (ICRA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages7
ISBN (Electronic)978-1-7281-7395-5
ISBN (Print)978-1-7281-7396-2
Publication statusPublished - 15 Sept 2020
Event2020 International Conference on Robotics and Automation - Virtual conference, France
Duration: 31 May 202031 Aug 2020

Publication series

ISSN (Print)1050-4729
ISSN (Electronic)2577-087X


Conference2020 International Conference on Robotics and Automation
Abbreviated titleICRA 2020
CityVirtual conference
Internet address


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