22 citations · 50 across the 10 of their papers we have counts for
4 papers · 1 filter
DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning
Hanchen Cui, Sergio Arnaud, Arjun Majumdar +5
Pretrained vision-language-action (VLA) policies show promising zero-shot generalization, but often fail under deployment-time distribution shift, leading to decreased robustness a…
Visuo-Tactile World Models
Carolina Higuera, Sergio Arnaud, Byron Boots +3
We introduce multi-task Visuo-Tactile World Models (VT-WM), which capture the physics of contact through touch reasoning. By complementing vision with tactile sensing, VT-WM better…
What do we learn from a large-scale study of pre-trained visual representations in sim and real environments?
Sneha Silwal, Karmesh Yadav, Tingfan Wu +10
We present a large empirical investigation on the use of pre-trained visual representations (PVRs) for training downstream policies that execute real-world tasks. Our study involve…
ASC: Adaptive Skill Coordination for Robotic Mobile Manipulation
Naoki Yokoyama, Alex Clegg, Joanne Truong +6
We present Adaptive Skill Coordination (ASC) -- an approach for accomplishing long-horizon tasks like mobile pick-and-place (i.e., navigating to an object, picking it, navigating t…