5 citations · 8 across the 4 of their papers we have counts for
4 papers
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…
EMOTION: Expressive Motion Sequence Generation for Humanoid Robots with In-Context Learning
Peide Huang, Yuhan Hu, Nataliya Nechyporenko +3
This paper introduces a framework, called EMOTION, for generating expressive motion sequences in humanoid robots, enhancing their ability to engage in humanlike non-verbal communic…