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Planar Robot Casting with Real2Sim2Real Self-Supervised Learning [article]

Vincent Lim, Huang Huang, Lawrence Yunliang Chen, Jonathan Wang, Jeffrey Ichnowski, Daniel Seita, Michael Laskey, Ken Goldberg
2021 arXiv   pre-print

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https://web.archive.org/web/20211117111354/https://arxiv.org/pdf/2111.04814v1.pdf

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To efficiently learn a PRC policy for a given cable, we propose Real2Sim2Real, a self-supervised framework that automatically collects physical trajectory examples to tune parameters of a dynamics simulator  ...  This paper explores the task of Planar Robot Casting (PRC): where one planar motion of a robot wrist holding one end of a cable causes the other end to slide across the plane toward a desired target.  ...  ACKNOWLEDGMENTS This research was performed at the AUTOLAB at UC Berkeley in affiliation with the Berkeley AI Research (BAIR) Lab and the CITRIS "People and Robots" (CPAR) Initiative.  ... 
arXiv:2111.04814v1 fatcat:pssckn6uubclnpa2ye6gg4aw5q
Citation

Vincent Lim, Huang Huang, Lawrence Yunliang Chen, Jonathan Wang, Jeffrey Ichnowski, Daniel Seita, Michael Laskey, Ken Goldberg. "Planar Robot Casting with Real2Sim2Real Self-Supervised Learning." arXiv (2021)