Low-cost imprecise robots achieve 80-90% success on six fine bimanual manipulation tasks using imitation learning with a new Action Chunking with Transformers algorithm trained on only 10 minutes of demonstrations.
Novoseller, Minho Hwang, Michael Laskey, Joseph Gon- zalez, and Ken Goldberg
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DLO-Lab supplies a differentiable simulator modeling DLO material properties, a task benchmark, and an agent for strategic grasping and long-horizon decomposition to advance robotic DLO manipulation.
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DLO-Lab: Benchmarking Deformable Linear Object Manipulations with Differentiable Physics
DLO-Lab supplies a differentiable simulator modeling DLO material properties, a task benchmark, and an agent for strategic grasping and long-horizon decomposition to advance robotic DLO manipulation.