Motion learning in variable environments using probabilistic flow tubes

Commanding an autonomous system through complex motions at a low level can be tedious or impractical for systems with many degrees of freedom. Allowing an operator to demonstrate the desired motions directly can often enable more intuitive and efficient interaction. Two challenges in the field of le...

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Bibliographic Details
Main Authors: Dong, Shuonan (Contributor), Williams, Brian Charles (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2013-09-24T20:41:09Z.
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