Assist system for remote manipulation of electric drills by the robot WAREC-1R using deep reinforcement learning

Xiao Sun*, Hiroshi Naito, Akio Namiki, Yang Liu, Takashi Matsuzawa, Atsuo Takanishi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Operation of tools has long been studied in robotics. Although appropriate hold of the tool by robots is the base of successful tool operation, it is not with ease especially for tools with complicated shape. In this paper, an assist system for a four-limbed robot is proposed for remote operation of reaching and grasping electric drills using deep reinforcement learning. Through comparative evaluation experiments, the increase of success rate for reaching and grasping is verified and the decrease in both physical and mental workload of the operator is also validated by the index of NASA-TLX.

Original languageEnglish
Pages (from-to)365-376
Number of pages12
JournalRobotica
Volume40
Issue number2
DOIs
Publication statusPublished - 2022 Feb 4

Keywords

  • Deep reinforcement learning
  • Manipulation
  • Remote operation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications

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