most citedLearning a Shape-adaptive Assist-as-needed Rehabilitation Policy from Therapist-informed Input

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cs.RO2025

Tele-rehabilitation with online skill transfer and adaptation in

Tianle Ni, Xiao Chen, Hamid Sadeghian +1

This paper proposes a tele-teaching framework for the domain of robot-assisted tele-rehabilitation. The system connects two robotic manipulators on therapist and patient side via b…

cs.RO2025

Prompt2Auto: From Motion Prompt to Automated Control via Geometry-Invariant One-Shot Gaussian Process Learning

Zewen Yang, Xiaobing Dai, Dongfa Zhang +5

Learning from demonstration allows robots to acquire complex skills from human demonstrations, but conventional approaches often require large datasets and fail to generalize acros…

cs.RO2025

RCM Constraint-Consistent Dynamic Control in Surgical Robots

Yu Li, Hamid Sadeghian, Zewen Yang +2

Robotic-assisted minimally invasive surgery (RAMIS) requires accurate enforcement of the remote center of motion (RCM) constraint to ensure safe tool motion through a trocar. Exist…

cs.RO2025

SafeFlow: Safe Robot Motion Planning with Flow Matching via Control Barrier Functions

Xiaobing Dai, Zewen Yang, Dian Yu +4

Recent advances in generative modeling have led to promising results in robot motion planning, particularly through diffusion and flow matching (FM)-based models that capture compl…

cs.RO2025

SharedAssembly: A Data Collection Approach via Shared Tele-Assembly

Yansong Wu, Xiao Chen, Yu Chen +4

High-precision, tight-clearance assembly demonstrations are indispensable for training tactile-aware robotic foundation models, yet their acquisition is heavily bottlenecked by the…

cs.RO2024

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…