Identification of a Step-And-Brake Controller of a Human Based on Prediction of Capturability

An explicit mathematical form of a human’s step-and-brake controller is identified through motion measurement of the human subject. The controller was originally designed for biped robots based on the reduced-order dynamics and the model predictive control scheme with the terminal capturability cond...

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Vydáno v:Frontiers in Robotics and AI Ročník 9; s. 729593
Hlavní autoři: Kojima, Miharu, Sugihara, Tomomichi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland Frontiers Media SA 28.04.2022
Frontiers Media S.A
Témata:
biped locomotion
capturability
COM-ZMP model
Electronic computers. Computer science
human motor control
Mechanical engineering and machinery
QA75.5-76.95
Robotics and AI
step-and-brake motion
system identification
TJ1-1570
COM-ZMP model
step-and-brake motion
biped locomotion
human motor control
capturability
system identification
ISSN:2296-9144, 2296-9144
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Shrnutí:An explicit mathematical form of a human’s step-and-brake controller is identified through motion measurement of the human subject. The controller was originally designed for biped robots based on the reduced-order dynamics and the model predictive control scheme with the terminal capturability condition, and is compatible with both stand-still and stepping motions. The minimal number of parameters facilitates the identification from measured trajectories of the center of mass and the zero-moment point of the human subject. In spite of the minimality, the result only suited the human’s behaviors well with slight modifications of the model by taking direction-dependency of the natural falling speed and the inertial torque about the center of mass into account. Furthermore, the parameters are successfully identified even from the first half of motion sequence, which means that the proposed method is available in designing on-the-fly systems to evaluate balancing abilities of humans and to assist balances of humans in walking.
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Reviewed by: Robert Griffin, Florida Institute for Human and Machine Cognition, United States
João Paulo Morais Ferreira, Superior Institute of Engineering of Coimbra (ISEC), Portugal
Edited by: Tadej Petric, Institut Jožef Stefan (IJS), Slovenia
Hassãne Gritli, University of Tunis, Tunisia
This article was submitted to Humanoid Robotics, a section of the journal Frontiers in Robotics and AI
ISSN:2296-9144
2296-9144
DOI:10.3389/frobt.2022.729593