8 papers
Point Bridge: 3D Representations for Cross Domain Policy Learning
Siddhant Haldar, Lars Johannsmeier, Lerrel Pinto +4
Robot foundation models are beginning to deliver on the promise of generalist robotic agents, yet progress remains constrained by the scarcity of large-scale real-world manipulatio…
DreamGen: Unlocking Generalization in Robot Learning through Video World Models
Joel Jang, Seonghyeon Ye, Zongyu Lin +25
We introduce DreamGen, a simple yet highly effective 4-stage pipeline for training robot policies that generalize across behaviors and environments through neural trajectories - sy…
DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation
Zhao Mandi, Yifan Hou, Dieter Fox +3
We study the problem of functional retargeting: learning dexterous manipulation policies to track object states from human hand-object demonstrations. We focus on long-horizon, bim…
Latent Action Pretraining from Videos
Seonghyeon Ye, Joel Jang, Byeongguk Jeon +13
We introduce Latent Action Pretraining for general Action models (LAPA), an unsupervised method for pretraining Vision-Language-Action (VLA) models without ground-truth robot actio…
GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
NVIDIA, :, Johan Bjorck +40
General-purpose robots need a versatile body and an intelligent mind. Recent advancements in humanoid robots have shown great promise as a hardware platform for building generalist…
SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment
Caelan Garrett, Ajay Mandlekar, Bowen Wen +1
Imitation learning from human demonstrations is an effective paradigm for robot manipulation, but acquiring large datasets is costly and resource-intensive, especially for long-hor…