Unified Push Recovery Fundamentals: Inspiration from Human Study
Christopher McGreavy, Kai Yuan, Daniel Gordon, Kang Tan, Wouter J Wolfslag, Sethu Vijayakumar, Zhibin Li
Abstract
Currently for balance recovery, humans outperform humanoid robots which use hand-designed controllers in terms of the diverse actions. This study aims to close this gap by finding core control principles that are shared across ankle, hip, toe and stepping strategies by formulating experiments to test human balance recoveries and define criteria to quantify the strategy in use. To reveal fundamental principles of balance strategies, our study shows that a minimum jerk controller can accurately replicate comparable human behaviour at the Centre of Mass level. Therefore, we formulate a general Model-Predictive Control (MPC) framework to produce recovery motions in any system, including legged machines, where the framework parameters are tuned for time-optimal performance in robotic systems.
BibTeX
@inproceedings{icra2020_unifiedpushrecov,
title = {Unified Push Recovery Fundamentals: Inspiration from Human Study},
author = {Christopher McGreavy and Kai Yuan and Daniel Gordon and Kang Tan and Wouter J Wolfslag and Sethu Vijayakumar and Zhibin Li},
booktitle = {ICRA 2020},
year = {2020}
}