TY - JOUR
T1 - Involuntary Stabilization in Discrete-Event Physical Human-Robot Interaction
AU - Muramatsu, Hisayoshi
AU - Itaguchi, Yoshihiro
AU - Katsura, Seiichiro
N1 - Funding Information:
This work was supported by JSPS KAKENHI under Grant 21H04566.
Publisher Copyright:
© 2013 IEEE.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Robots are used by humans not only as tools but also to interactively assist and cooperate with humans, thereby forming physical human-robot interactions. In these interactions, there is a risk that a feedback loop causes unstable force interaction, in which force escalation exposes a human to danger. Previous studies have analyzed the stability of voluntary interaction but have neglected involuntary behavior in the interaction. In contrast to the previous studies, this study considered the involuntary behavior: a human's force reproduction bias for discrete-event human-robot force interaction. We derived an asymptotic stability condition based on a mathematical bias model and found that the bias asymptotically stabilizes a human's implicit equilibrium point far from the implicit equilibrium point and destabilizes the point near the point. The bias model, convergence of the interaction toward the implicit equilibrium point, and divergence around the point were consistently verified via behavioral experiments under three kinds of interactions using three different body parts: 1) a hand finger; 2) wrist; and 3) foot. Our results imply that humans implicitly secure a stable and close relationship between themselves and robots with their involuntary behavior.
AB - Robots are used by humans not only as tools but also to interactively assist and cooperate with humans, thereby forming physical human-robot interactions. In these interactions, there is a risk that a feedback loop causes unstable force interaction, in which force escalation exposes a human to danger. Previous studies have analyzed the stability of voluntary interaction but have neglected involuntary behavior in the interaction. In contrast to the previous studies, this study considered the involuntary behavior: a human's force reproduction bias for discrete-event human-robot force interaction. We derived an asymptotic stability condition based on a mathematical bias model and found that the bias asymptotically stabilizes a human's implicit equilibrium point far from the implicit equilibrium point and destabilizes the point near the point. The bias model, convergence of the interaction toward the implicit equilibrium point, and divergence around the point were consistently verified via behavioral experiments under three kinds of interactions using three different body parts: 1) a hand finger; 2) wrist; and 3) foot. Our results imply that humans implicitly secure a stable and close relationship between themselves and robots with their involuntary behavior.
KW - Force control
KW - force reproduction
KW - human behavior
KW - human-robot interaction
KW - perception and sychophysics
KW - physical human-robot interaction
KW - stability
UR - http://www.scopus.com/inward/record.url?scp=85134222780&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134222780&partnerID=8YFLogxK
U2 - 10.1109/TSMC.2022.3184960
DO - 10.1109/TSMC.2022.3184960
M3 - Article
AN - SCOPUS:85134222780
SN - 2168-2216
VL - 53
SP - 576
EP - 587
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 1
ER -