Deep learning-based human motion recognition for predictive context-aware human-robot collaboration

Peng Wang, Hongyi Liu, Lihui Wang, Robert X. Gao

Research output: Contribution to journalArticlepeer-review

101 Scopus citations

Abstract

Timely context awareness is key to improving operation efficiency and safety in human-robot collaboration (HRC) for intelligent manufacturing. Visual observation of human workers’ motion provides informative clues about the specific tasks to be performed, thus can be explored for establishing accurate and reliable context awareness. Towards this goal, this paper investigates deep learning as a data driven technique for continuous human motion analysis and future HRC needs prediction, leading to improved robot planning and control in accomplishing a shared task. A case study in engine assembly is carried out to validate the feasibility of the proposed method.

Original languageEnglish
Pages (from-to)17-20
Number of pages4
JournalCIRP Annals - Manufacturing Technology
Volume67
Issue number1
DOIs
StatePublished - Jan 1 2018

Keywords

  • Machine learning
  • Motion
  • Predictive model

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

Fingerprint

Dive into the research topics of 'Deep learning-based human motion recognition for predictive context-aware human-robot collaboration'. Together they form a unique fingerprint.

Cite this