A Study of Shared-Control With Bilateral Feedback for Obstacle Avoidance in Whole-Body Telelocomotion of a Wheeled Humanoid

Dong Hoon Baek, Yu Chen Chang, Joao Ramos

Research output: Contribution to journalArticlepeer-review

Abstract

Teleoperation has emerged as an alternative solution to fully-autonomous systems for achieving human-level capabilities on humanoids. Specifically, teleoperation with whole-body control is a promising hands-free strategy to command humanoids but requires more physical and mental demand. To mitigate this limitation, researchers have proposed shared-control methods incorporating robot decision-making to aid humans on low-level tasks, further reducing operation effort. However, shared-control methods for wheeled humanoid telelocomotion on a whole-body level has yet to be explored. In this work, we explore how whole-body bilateral feedback with haptics affects the performance of different shared-control methods for obstacle avoidance in diverse environments. A time-derivative Sigmoid function (TDSF) is implemented to generate more intuitive haptic feedback from obstacles. Comprehensive human experiments were conducted and the results concluded that bilateral feedback enhances the whole-body telelocomotion performance in unfamiliar environments but could reduce performance in familiar environments. Conveying the robot's intention through haptics showed further improvements since the operator can utilize the feedback for reactive short-distance planning and visual feedback for long-distance planning.

Original languageEnglish (US)
Pages (from-to)6979-6986
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume8
Issue number11
DOIs
StatePublished - Nov 1 2023
Externally publishedYes

Keywords

  • Shared-control
  • bilateral feedback
  • humanoid robot
  • obstacle avoidance
  • whole-body telelocomotion

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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