5 papers · 1 filter
What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?
Richard Li, Aditya Prakash, Andrew Wen +3
Human video datasets used for cotraining robot manipulation policies largely consist of curated demonstrations where motions are orchestrated to resemble robot behavior and 3D hand…
HERO: Learning Humanoid End-Effector Control for Visual Whole-Body Open-Vocabulary Object Grasping
Runpei Dong, Ziyan Li, Arjun Gupta +2
Visual loco-manipulation of arbitrary in-the-wild objects requires accurate end-effector (EE) control and a generalizable understanding of the scene from visual inputs (eg, RGB-D i…
Precise Mobile Manipulation of Small Everyday Objects
Arjun Gupta, Rishik Sathua, Saurabh Gupta
Many everyday mobile manipulation tasks require precise interaction with small objects, such as grasping a knob to open a cabinet or pressing a light switch. In this paper, we deve…
Opening Articulated Structures in the Real World
Arjun Gupta, Michelle Zhang, Rishik Sathua +1
What does it take to build mobile manipulation systems that can competently operate on previously unseen objects in previously unseen environments? This work answers this question…
Diffusion Meets DAgger: Supercharging Eye-in-hand Imitation Learning
Xiaoyu Zhang, Matthew Chang, Pranav Kumar +1
A common failure mode for policies trained with imitation is compounding execution errors at test time. When the learned policy encounters states that are not present in the expert…