Chinese Journal of Intelligent Science and Technology ›› 2019, Vol. 1 ›› Issue (3): 280-286.doi: 10.11959/j.issn.2096-6652.201933

• Regular Papers • Previous Articles     Next Articles

Research and validation of human-in-the-loop hybrid-augmented intelligence in Sawyer

Haijun FU1,2,Shichao CHEN1,3,Yilun LIN1,Gang XIONG1,Bin HU1()   

  1. 1 The State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China
    2 School of Artificial Intelligence,University of Chinese Academy of Sciences,Beijing 100049,China
    3 Macau University of Science and Technology,Macau 999078,China
  • Revised:2019-08-01 Online:2019-09-20 Published:2019-12-17
  • Supported by:
    The National Key Research and Development Program of China(2018YFB1702701);The National Natural Science Foundation of China(61773381);The National Natural Science Foundation of China(61773382);The National Natural Science Foundation of China(61533019);The National Natural Science Foundation of China(61872365);Beijing Natural Science Foundation(4182065)


Machine learning predicts the future through the patterns of past data,and has gained a lot of research and application in recent years.However,it’s far away from human in dynamic,non-complete,and unstructured information processes.Therefore human decision-making,combined with machine learning,knowledge base were introduced in this paper and a human-in-the-loop hybrid-augmented intelligence closed-loop system was built.Based on Sawyer collaborative robot,a human-machine collaboration experiment platform was built,and a grasping experiment was designed.It turns out that the Sawyer,which is introduced human intelligence,performs better in dealing with unstructured environments than that only machine learning is used.

Key words: human-machine collaboration, Sawyer, collaborative robot

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