A Multisensory and Support Vector Machine Based Teleoperate Robotic Arm

  • Meng Chu
  • , Ziang Cui
  • , Shuo Gao*
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Teleoperation is a crucial function for human-robotic cooperation. This paper presents an advanced multisensory controlling robotic arm based on flexible electromyography (EMG) sensor and inertial measurement unit (IMU). Signals from these sensors map to different degrees of freedom (DOFs) of the human body. And a support vector machine based algorithm process the data sampling from the sensors to classify three standard muscle modes. This method could reach a high accuracy of 98.7%. Through an adaptive control method based control algorithm, one user could use the robotic arm to finish one task with an average time of 37.6s. This article demonstrates a feasible means for robotic teleoperation by integrating multiple wearable sensing techniques and the comprehensive control algorithm, potentially advancing the development of human-robotic cooperation.

Original languageEnglish
Title of host publicationFLEPS 2021 - IEEE International Conference on Flexible and Printable Sensors and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728191737
DOIs
StatePublished - 20 Jun 2021
Event2021 IEEE International Conference on Flexible and Printable Sensors and Systems, FLEPS 2021 - Virtual, Online
Duration: 20 Jun 202123 Jun 2021

Publication series

NameFLEPS 2021 - IEEE International Conference on Flexible and Printable Sensors and Systems

Conference

Conference2021 IEEE International Conference on Flexible and Printable Sensors and Systems, FLEPS 2021
CityVirtual, Online
Period20/06/2123/06/21

Keywords

  • Electromyography
  • Inertial Measurement Unit
  • Machine Learning
  • Multisensory
  • Robotic Teleoperation

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