May 7, 2024, 4:43 a.m. | ALOHA 2 Team, Jorge Aldaco, Travis Armstrong, Robert Baruch, Jeff Bingham, Sanky Chan, Kenneth Draper, Debidatta Dwibedi, Chelsea Finn, Pete Florence,

cs.LG updates on arXiv.org arxiv.org

arXiv:2405.02292v1 Announce Type: cross
Abstract: Diverse demonstration datasets have powered significant advances in robot learning, but the dexterity and scale of such data can be limited by the hardware cost, the hardware robustness, and the ease of teleoperation. We introduce ALOHA 2, an enhanced version of ALOHA that has greater performance, ergonomics, and robustness compared to the original design. To accelerate research in large-scale bimanual manipulation, we open source all hardware designs of ALOHA 2 with a detailed tutorial, together …

abstract advances aloha arxiv cost cs.lg cs.ro data datasets diverse hardware low performance robot robustness scale teleoperation type

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