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Vision-Based Approximate Estimation of Muscle Activation Patterns for Tele-Impedance

Ahn, Hyemin and Michel, Youssef and Eiband, Thomas and Lee, Dongheui (2023) Vision-Based Approximate Estimation of Muscle Activation Patterns for Tele-Impedance. IEEE Robotics and Automation Letters, 8 (8), pp. 5220-5227. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LRA.2023.3293275. ISSN 2377-3766.

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Official URL: https://ieeexplore.ieee.org/document/10175383


It lies in human nature to properly adjust the muscle force to perform a given task successfully. While transferring this control ability to robots has been a big concern among researchers, there is no attempt to make a robot learn how to control the impedance solely based on visual observations. Rather, the research on tele-impedance usually relies on special devices such as EMG sensors, which have less accessibility as well as less generalization ability compared to simple RGB webcams. In this letter, we propose a system for a vision-based tele-impedance control of robots, based on the approximately estimated muscle activation patterns. These patterns are obtained from the proposed deep learning-based model, which uses RGB images from an affordable commercial webcam as inputs. It is remarkable that our model does not require humans to apply any visible markers to their muscles. Experimental results show that our model enables a robot to mimic how humans adjust their muscle force to perform a given task successfully. Although our experiments are focused on tele-impedance control, our system can also provide a baseline for improvement of vision-based learning from demonstration, which would also incorporate the information of variable stiffness control for successful task execution.

Item URL in elib:https://elib.dlr.de/197475/
Document Type:Article
Title:Vision-Based Approximate Estimation of Muscle Activation Patterns for Tele-Impedance
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Ahn, HyeminUNSPECIFIEDhttps://orcid.org/0000-0001-8081-6023UNSPECIFIED
Eiband, ThomasUNSPECIFIEDhttps://orcid.org/0000-0002-1074-9504UNSPECIFIED
Lee, DongheuiUNSPECIFIEDhttps://orcid.org/0000-0003-1897-7664UNSPECIFIED
Date:7 July 2023
Journal or Publication Title:IEEE Robotics and Automation Letters
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 5220-5227
Publisher:IEEE - Institute of Electrical and Electronics Engineers
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - Basic Technologies [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Strobl, Dr. Klaus H.
Deposited On:22 Sep 2023 11:56
Last Modified:22 Sep 2023 11:56

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