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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
