51 citations · 87 across the 22 of their papers we have counts for
8 papers · 1 filter
Motion Planning for Robotics: A Review for Sampling-based Planners
Liding Zhang, Kuanqi Cai, Zewei Sun +5
Recent advancements in robotics have transformed industries such as manufacturing, logistics, surgery, and planetary exploration. A key challenge is developing efficient motion pla…
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…
LEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks
Kejia Chen, Zheng Shen, Yue Zhang +5
Large Language Models (LLMs) have gained popularity in task planning for long-horizon manipulation tasks. To enhance the validity of LLM-generated plans, visual demonstrations and…
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…
Visuo-Tactile Exploration of Unknown Rigid 3D Curvatures by Vision-Augmented Unified Force-Impedance Control
Kübra Karacan, Anran Zhang, Hamid Sadeghian +2
Despite recent advancements in torque-controlled tactile robots, integrating them into manufacturing settings remains challenging, particularly in complex environments. Simplifying…
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…