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Deep learning-based human motion recognition for predictive context-aware human-robot collaboration
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DOI：10.1016/j.cirp.2018.04.066.png)
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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. (C) 2018 Published by Elsevier Ltd on behalf of CIRP.
Keyword:
Motion
Predictive model
Machine learning
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分享收藏RETRACTED: Static hand gesture recognition using neural networks (Retracted article. See vol.47,pg.561,2017)收回: 使用神经网络进行静态手势识别 (收回的文章。请参阅vol.47，pg.561，2017)
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