Synthesis of Robot Hand Skills Powered by Crowdsourced Learning

Leidi Zhao, Raheem Lawhorn, Cong Wang, Lu Lu, Bo Ouyang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Crowdsourcing has shown great potentials in artificial intelligence. Continuous learning from a large group of mentors breaks the limit of learning from one or a few mentors in individual cases, and has achieved success in image recognition, translation and many other cyber applications. We bring the power of crowdsourcing to robot physical intelligence and introduce a learning method that allows robots to synthesize new physical skills using knowledge acquired from crowd-sourced human mentors. In addition, we provide a solution to sustainably manage a continuously growing massive knowledge library. The method is validated using a virtual reality interface and a simulated test of robot in-hand manipulation. The work has the potential of robotizing many demanding tasks that are currently hard to automate due to the demanding requirement of hand skills. The effectiveness of crowdsourced learning is evaluated by studying the success rate of new skill synthesis and the performance of the synthesized skills.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Mechatronics, ICM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages211-216
Number of pages6
ISBN (Electronic)9781538669594
DOIs
StatePublished - May 24 2019
Event2019 IEEE International Conference on Mechatronics, ICM 2019 - Ilmenau, Germany
Duration: Mar 18 2019Mar 20 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Mechatronics, ICM 2019

Conference

Conference2019 IEEE International Conference on Mechatronics, ICM 2019
CountryGermany
CityIlmenau
Period3/18/193/20/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Automotive Engineering
  • Mechanical Engineering
  • Control and Optimization
  • Industrial and Manufacturing Engineering

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