57 citations · 59 across the 8 of their papers we have counts for
4 papers · 1 filter
GraspGraphNet: Graph-Structured Multi-Embodiment Dexterous Grasp Generation
Yeonseo Lee, Taeyeop Lee, Hyosup Shin +2
Dexterous grasp generation across robot hands is challenging because hands differ in kinematic topology, actuation dimensions, and native command spaces. We introduce GraspGraphNet…
XGrasp: Gripper-Aware Grasp Detection with Multi-Gripper Data Generation
Yeonseo Lee, Jungwook Mun, Hyosup Shin +4
Real-world robotic systems frequently require diverse end-effectors for different tasks, however most existing grasp detection methods are optimized for a single gripper type, dema…
DeLTa: Demonstration and Language-Guided Novel Transparent Object Manipulation
Taeyeop Lee, Gyuree Kang, Bowen Wen +5
Despite the prevalence of transparent object interactions in human everyday life, transparent robotic manipulation research remains limited to short-horizon tasks and basic graspin…
GraspClutter6D: A Large-scale Real-world Dataset for Robust Perception and Grasping in Cluttered Scenes
Seunghyeok Back, Joosoon Lee, Kangmin Kim +8
Robust grasping in cluttered environments remains an open challenge in robotics. While benchmark datasets have significantly advanced deep learning methods, they mainly focus on si…