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…
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…
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…