8 citations · 8 across the 3 of their papers we have counts for
3 papers · 1 filter
VLK: Learning Humanoid Loco-Manipulation from Synthetic Interactions in Reconstructed Scenes
Yen-Jen Wang, Jiaman Li, Sirui Chen +9
Perception-based humanoid loco-manipulation requires connecting egocentric observations and task instructions to whole-body motion. Learning this mapping requires synchronized egoc…
Flow Policy Gradients for Robot Control
Brent Yi, Hongsuk Choi, Himanshu Gaurav Singh +9
Likelihood-based policy gradient methods are the dominant approach for training robot control policies from rewards. These methods rely on differentiable action likelihoods, which…
BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion
Qiayuan Liao, Takara E. Truong, Xiaoyu Huang +4
The human-like form of humanoid robots positions them uniquely to achieve the agility and versatility in motor skills that humans possess. Learning from human demonstrations offers…