2 citations · 5 across the 13 of their papers we have counts for
5 papers · 1 filter
Behavior Tree Generation using Large Language Models for Sequential Manipulation Planning with Human Instructions and Feedback
Jicong Ao, Yansong Wu, Fan Wu +1
In this work, we propose an LLM-based BT generation framework to leverage the strengths of both for sequential manipulation planning. To enable human-robot collaborative task plann…
TacDiffusion: Force-domain Diffusion Policy for Precise Tactile Manipulation
Yansong Wu, Zongxie Chen, Fan Wu +6
Assembly is a crucial skill for robots in both modern manufacturing and service robotics. However, mastering transferable insertion skills that can handle a variety of high-precisi…
LLM-as-BT-Planner: Leveraging LLMs for Behavior Tree Generation in Robot Task Planning
Jicong Ao, Fan Wu, Yansong Wu +2
Robotic assembly tasks remain an open challenge due to their long horizon nature and complex part relations. Behavior trees (BTs) are increasingly used in robot task planning for t…
Tactile-Morph Skills: Energy-Based Control Meets Data-Driven Learning
Anran Zhang, Kübra Karacan, Hamid Sadeghian +3
Robotic manipulation is essential for modernizing factories and automating industrial tasks like polishing, which require advanced tactile abilities. These robots must be easily se…
Real-time Contact State Estimation in Shape Control of Deformable Linear Objects under Small Environmental Constraints
Kejia Chen, Zhenshan Bing, Yansong Wu +4
Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust…