243 citations · 320 across the 14 of their papers we have counts for
7 papers · 1 filter
ManipForce: Force-Guided Policy Learning with Frequency-Aware Representation for Contact-Rich Manipulation
Geonhyup Lee, Yeongjin Lee, Kangmin Kim +4
Contact-rich manipulation tasks such as precision assembly require precise control of interaction forces, yet existing imitation learning methods rely mainly on vision-only demonst…
BiGraspFormer: End-to-End Bimanual Grasp Transformer
Kangmin Kim, Seunghyeok Back, Geonhyup Lee +3
Bimanual grasping is essential for robots to handle large and complex objects. However, existing methods either focus solely on single-arm grasping or employ separate grasp generat…
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…
GraspSAM: When Segment Anything Model Meets Grasp Detection
Sangjun Noh, Jongwon Kim, Dongwoo Nam +3
Grasp detection requires flexibility to handle objects of various shapes without relying on prior knowledge of the object, while also offering intuitive, user-guided control. This…
Learning to Place Unseen Objects Stably using a Large-scale Simulation
Sangjun Noh, Raeyoung Kang, Taewon Kim +3
Object placement is a fundamental task for robots, yet it remains challenging for partially observed objects. Existing methods for object placement have limitations, such as the re…
Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling
Seunghyeok Back, Joosoon Lee, Taewon Kim +4
Instance-aware segmentation of unseen objects is essential for a robotic system in an unstructured environment. Although previous works achieved encouraging results, they were limi…
Object Detection for Understanding Assembly Instruction Using Context-aware Data Augmentation and Cascade Mask R-CNN
Joosoon Lee, Seongju Lee, Seunghyeok Back +2
Understanding assembly instruction has the potential to enhance the robot s task planning ability and enables advanced robotic applications. To recognize the key components from th…