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 language | English |
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Pages (from-to) | 17-20 |
Number of pages | 4 |
Journal | CIRP Annals |
Volume | 67 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2018 |
Bibliographical note
Publisher Copyright:© 2018
Keywords
- Machine learning
- Motion
- Predictive model
ASJC Scopus subject areas
- Mechanical Engineering
- Industrial and Manufacturing Engineering