Data-oriented state space discretization for crowdsourced robot learning of physical skills

Document Type

Article

Publication Date

4-1-2021

Abstract

This work discusses a crowdsourced learning scheme for robot physical intelligence. Using a large amount of data from crowdsourced mentors, the scheme allows robots to synthesize new physical skills that are never demonstrated or only partially demonstrated without heavy re-training. The learning scheme features a data management method to sustainably manage continuously collected data and a growing knowledge library. The method is validated using a simulated challenge of solving a bottle puzzle. The learning scheme aims at realizing ubiquitous robot learning of physical skills and has the potential of automating many demanding tasks that are currently hard to robotize.

Identifier

85096025364 (Scopus)

Publication Title

ASME Letters in Dynamic Systems and Control

External Full Text Location

https://doi.org/10.1115/1.4047961

e-ISSN

26896125

ISSN

26896117

Issue

2

Volume

1

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