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Preliminary Exploration of Antagonistic Vibrotactile Feedback to Improve Force Regulation in Teleoperated Bimanual Manipulation

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

Abstract

State of the art robotic systems still struggle to accomplish complex tasks, such as bimanual manipulation, in unpredictable environments due to limitations in sensing, adaptability, and control - leading to artificially restricted autonomous system performance. This research addresses this limitation by introducing a novel metric for quantifying antagonistic internal forces during teleoperated bimanual manipulation, conveyed through minimalistic vibrotactile feedback (VF) to the operator. Experimental tests demonstrated that integrating the proposed metric through VF improved internal force regulation, reducing average internal forces by approximately 39.5% and decreasing force variability by 52.1% compared to trials without feedback. Introducing VF exhibited an increased number of occurrences of payload drops - indicative of operators pushing closer to operational limits. These findings confirm the proposed metric delivered through minimalistic VF substantially enhances teleoperated manipulation, providing a promising avenue for safer, more intuitive robotic operations in dynamic and uncertain environments.

Original languageEnglish (US)
Title of host publication2025 IEEE-RAS 24th International Conference on Humanoid Robots, Humanoids 2025
PublisherIEEE Computer Society
Pages1211-1218
Number of pages8
ISBN (Electronic)9798331598693
DOIs
StatePublished - 2025
Event24th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2025 - Seoul, Korea, Republic of
Duration: Sep 30 2025Oct 2 2025

Publication series

NameIEEE-RAS International Conference on Humanoid Robots
ISSN (Print)2164-0572
ISSN (Electronic)2164-0580

Conference

Conference24th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2025
Country/TerritoryKorea, Republic of
CitySeoul
Period9/30/2510/2/25

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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