13 citations · 23 across the 6 of their papers we have counts for
3 papers · 1 filter
Learned Neural Physics Simulation for Articulated 3D Human Pose Reconstruction
Mykhaylo Andriluka, Baruch Tabanpour, C. Daniel Freeman +1
We propose a novel neural network approach, LARP (Learned Articulated Rigid body Physics), to model the dynamics of articulated human motion with contact. Our goal is to develop a…
ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation
ALOHA 2 Team, Jorge Aldaco, Travis Armstrong +23
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 robus…
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Jacky Liang, Fei Xia, Wenhao Yu +47
Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot beha…