3 papers
cs.RO2026
ChainSplat: A Physics-Inspired Screw-Theoretic Model for Learning Deformable Linear Object Dynamics from Multi-View RGB Videos
Seungyeon Kim, Noémie Jaquier
Identifying the underlying dynamics and 3D geometry of deformable linear objects (DLOs), such as cables, ropes, and hoses, is essential for accurate robotic manipulation, but remai…
cs.RO2025
ScrewSplat: An End-to-End Method for Articulated Object Recognition
Seungyeon Kim, Junsu Ha, Young Hun Kim +2
Articulated object recognition -- the task of identifying both the geometry and kinematic joints of objects with movable parts -- is essential for enabling robots to interact with…
cs.RO2024
Motion Manifold Flow Primitives for Task-Conditioned Trajectory Generation under Complex Task-Motion Dependencies
Yonghyeon Lee, Byeongho Lee, Seungyeon Kim +1
Effective movement primitives should be capable of encoding and generating a rich repertoire of trajectories -- typically collected from human demonstrations -- conditioned on task…