Home > Research > Publications & Outputs > A review on interaction control for contact rob...

Research

Associated organisational units

Links

Text available via DOI:

View graph of relations

A review on interaction control for contact robots through intent detection

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

A review on interaction control for contact robots through intent detection. / Li, Yanan; Sena, Aran; Wang, Ziwei et al.
In: Progress in Biomedical Engineering, Vol. 4, No. 3, 032004, 09.08.2022.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Li, Y, Sena, A, Wang, Z, Xing, X, Babič, J, Asseldonk, E & Burdet, E 2022, 'A review on interaction control for contact robots through intent detection', Progress in Biomedical Engineering, vol. 4, no. 3, 032004. https://doi.org/10.1088/2516-1091/ac8193

APA

Li, Y., Sena, A., Wang, Z., Xing, X., Babič, J., Asseldonk, E., & Burdet, E. (2022). A review on interaction control for contact robots through intent detection. Progress in Biomedical Engineering, 4(3), Article 032004. https://doi.org/10.1088/2516-1091/ac8193

Vancouver

Li Y, Sena A, Wang Z, Xing X, Babič J, Asseldonk E et al. A review on interaction control for contact robots through intent detection. Progress in Biomedical Engineering. 2022 Aug 9;4(3):032004. Epub 2022 Jul 31. doi: 10.1088/2516-1091/ac8193

Author

Li, Yanan ; Sena, Aran ; Wang, Ziwei et al. / A review on interaction control for contact robots through intent detection. In: Progress in Biomedical Engineering. 2022 ; Vol. 4, No. 3.

Bibtex

@article{5183398ce8894a72bd9eb99854bfb5c3,
title = "A review on interaction control for contact robots through intent detection",
abstract = "Interaction control presents opportunities for contact robots physically interacting with their human user, such as assistance targeted to each human user, communication of goals to enable effective teamwork, and task-directed motion resistance in physical training and rehabilitation contexts. Here we review the burgeoning field of interaction control in the control theory and machine learning communities, by analysing the exchange of haptic information between the robot and its human user, and how they share the task effort. We first review the estimation and learning methods to predict the human user intent with the large uncertainty, variability and noise and limited observation of human motion. Based on this motion intent core, typical interaction control strategies are described using a homotopy of shared control parameters. Recent methods of haptic communication and game theory are then presented to consider the co-adaptation of human and robot control and yield versatile interactive control as observed between humans. Finally, the limitations of the presented state of the art are discussed and directions for future research are outlined.",
author = "Yanan Li and Aran Sena and Ziwei Wang and Xueyan Xing and Jan Babi{\v c} and Edwin Asseldonk and Etienne Burdet",
year = "2022",
month = aug,
day = "9",
doi = "10.1088/2516-1091/ac8193",
language = "English",
volume = "4",
journal = "Progress in Biomedical Engineering",
issn = "2516-1091",
publisher = "IOP Publishing Ltd.",
number = "3",

}

RIS

TY - JOUR

T1 - A review on interaction control for contact robots through intent detection

AU - Li, Yanan

AU - Sena, Aran

AU - Wang, Ziwei

AU - Xing, Xueyan

AU - Babič, Jan

AU - Asseldonk, Edwin

AU - Burdet, Etienne

PY - 2022/8/9

Y1 - 2022/8/9

N2 - Interaction control presents opportunities for contact robots physically interacting with their human user, such as assistance targeted to each human user, communication of goals to enable effective teamwork, and task-directed motion resistance in physical training and rehabilitation contexts. Here we review the burgeoning field of interaction control in the control theory and machine learning communities, by analysing the exchange of haptic information between the robot and its human user, and how they share the task effort. We first review the estimation and learning methods to predict the human user intent with the large uncertainty, variability and noise and limited observation of human motion. Based on this motion intent core, typical interaction control strategies are described using a homotopy of shared control parameters. Recent methods of haptic communication and game theory are then presented to consider the co-adaptation of human and robot control and yield versatile interactive control as observed between humans. Finally, the limitations of the presented state of the art are discussed and directions for future research are outlined.

AB - Interaction control presents opportunities for contact robots physically interacting with their human user, such as assistance targeted to each human user, communication of goals to enable effective teamwork, and task-directed motion resistance in physical training and rehabilitation contexts. Here we review the burgeoning field of interaction control in the control theory and machine learning communities, by analysing the exchange of haptic information between the robot and its human user, and how they share the task effort. We first review the estimation and learning methods to predict the human user intent with the large uncertainty, variability and noise and limited observation of human motion. Based on this motion intent core, typical interaction control strategies are described using a homotopy of shared control parameters. Recent methods of haptic communication and game theory are then presented to consider the co-adaptation of human and robot control and yield versatile interactive control as observed between humans. Finally, the limitations of the presented state of the art are discussed and directions for future research are outlined.

U2 - 10.1088/2516-1091/ac8193

DO - 10.1088/2516-1091/ac8193

M3 - Journal article

VL - 4

JO - Progress in Biomedical Engineering

JF - Progress in Biomedical Engineering

SN - 2516-1091

IS - 3

M1 - 032004

ER -