206 citations · 320 across the 6 of their papers we have counts for
6 papers
Vision in Action: Learning Active Perception from Human Demonstrations
Haoyu Xiong, Xiaomeng Xu, Jimmy Wu +3
We present Vision in Action (ViA), an active perception system for bimanual robot manipulation. ViA learns task-relevant active perceptual strategies (e.g., searching, tracking, an…
TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
Jimmy Wu, William Chong, Robert Holmberg +6
Exploiting the promise of recent advances in imitation learning for mobile manipulation will require the collection of large numbers of human-guided demonstrations. This paper prop…
TidyBot: Personalized Robot Assistance with Large Language Models
Jimmy Wu, Rika Antonova, Adam Kan +6
For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios. In this work, we investigate persona…
Learning Pneumatic Non-Prehensile Manipulation with a Mobile Blower
Jimmy Wu, Xingyuan Sun, Andy Zeng +3
We investigate pneumatic non-prehensile manipulation (i.e., blowing) as a means of efficiently moving scattered objects into a target receptacle. Due to the chaotic nature of aerod…
Spatial Intention Maps for Multi-Agent Mobile Manipulation
Jimmy Wu, Xingyuan Sun, Andy Zeng +3
The ability to communicate intention enables decentralized multi-agent robots to collaborate while performing physical tasks. In this work, we present spatial intention maps, a new…
Spatial Action Maps for Mobile Manipulation
Jimmy Wu, Xingyuan Sun, Andy Zeng +4
Typical end-to-end formulations for learning robotic navigation involve predicting a small set of steering command actions (e.g., step forward, turn left, turn right, etc.) from im…