Publications (20)
EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data
Ruijie Zheng, Dantong Niu, Yuqi Xie +12
Human behavior is among the most scalable sources of data for learning physical intelligence, yet how to effectively leverage it for dexterous manipulation remains unclear. While p…
Blox-Net: Generative Design-for-Robot-Assembly Using VLM Supervision, Physics Simulation, and a Robot with Reset
Andrew Goldberg, Kavish Kondap, Tianshuang Qiu +7
Generative AI systems have shown impressive capabilities in creating text, code, and images. Inspired by the rich history of research in industrial ''Design for Assembly'', we intr…
Safe Self-Supervised Learning in Real of Visuo-Tactile Feedback Policies for Industrial Insertion
Letian Fu, Huang Huang, Lars Berscheid +3
Industrial insertion tasks are often performed repetitively with parts that are subject to tight tolerances and prone to breakage. Learning an industrial insertion policy in real i…
Mechanical Search on Shelves using a Novel "Bluction" Tool
Huang Huang, Michael Danielczuk, Chung Min Kim +6
Shelves are common in homes, warehouses, and commercial settings due to their storage efficiency. However, this efficiency comes at the cost of reduced visibility and accessibility…
Rethinking Patch Dependence for Masked Autoencoders
Letian Fu, Long Lian, Renhao Wang +6
In this work, we examine the impact of inter-patch dependencies in the decoder of masked autoencoders (MAE) on representation learning. We decompose the decoding mechanism for mask…
In-Context Imitation Learning via Next-Token Prediction
Letian Fu, Huang Huang, Gaurav Datta +5
We explore how to enhance next-token prediction models to perform in-context imitation learning on a real robot, where the robot executes new tasks by interpreting contextual infor…