5 citations · 5 across the 4 of their papers we have counts for
5 papers
FineART: Fine-Grained Annotated Robotic Trajectory Dataset and Vision-Language-Action Model for Bimanual Manipulation
Jade Choghari, Pepijn Kooijmans, Mansi Agarwal +8
Robots operating in real-world environments must often execute complex, multi-step bimanual tasks over long horizons rather than single, isolated actions. Current manipulation data…
MoMo: Dial Motion Mode in Robot Manipulation with Spatiotemporal Action Tokenization
Yuhan Hu, Hugues Thomas, Peide Huang +3
To operate effectively across diverse contexts, robots must not only perform manipulation tasks accurately but also adapt how their actions unfold to the task, object, and interact…
EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video
Ryan Hoque, Peide Huang, David J. Yoon +2
Imitation learning for manipulation has a well-known data scarcity problem. Unlike natural language and 2D computer vision, there is no Internet-scale corpus of data for dexterous…
ELEGNT: Expressive and Functional Movement Design for Non-anthropomorphic Robot
Yuhan Hu, Peide Huang, Mouli Sivapurapu +1
Nonverbal behaviors such as posture, gestures, and gaze are essential for conveying internal states, both consciously and unconsciously, in human interaction. For robots to interac…
ARMADA: Augmented Reality for Robot Manipulation and Robot-Free Data Acquisition
Nataliya Nechyporenko, Ryan Hoque, Christopher Webb +2
Teleoperation for robot imitation learning is bottlenecked by hardware availability. Can high-quality robot data be collected without a physical robot? We present a system for augm…