An EMG-controlled mobile robot based on a multi-layered non-contact impedance model

Taro Shibanoki, Masaru Sasaki, Toshio Tsuji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an obstacle avoidance method for EMG-controlled mobile robots based on a noncontact impedance model. The proposed system can voluntarily control a mobile robot by classifying EMG signals using a recurrent probabilistic neural network and can avoid obstacles without user handling based on virtual repulsive force through a multi-layered non-contact impedance model. In the experiments, two obstacles were arranged in the path of the mobile robot, and the participant was asked to control the robot toward a target. The robot passed through the obstacles smoothly without any avoidance operations, indicating that the proposed system could be used for obstacle avoidance in mobile robots.

Original languageEnglish
Title of host publicationLifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages126-127
Number of pages2
ISBN (Electronic)9781665418751
DOIs
Publication statusPublished - Mar 9 2021
Externally publishedYes
Event3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021 - Nara, Japan
Duration: Mar 9 2021Mar 11 2021

Publication series

NameLifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies

Conference

Conference3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021
Country/TerritoryJapan
CityNara
Period3/9/213/11/21

Keywords

  • Collision avoidance
  • Electromyogram (EMG)
  • Noncontact impedance control
  • Recurrent probabilistic neural network

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health(social science)
  • Biochemistry
  • Artificial Intelligence
  • Computer Science Applications

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