Changhyun Choi

収録論文 22本 ・ フィジカルAI/ロボット学習

※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。

論文

• LAMP: Lane-Aligned Motion Primitives for Feasible Trajectory Prediction
  2026/6/1
• Temporal Action Representation Learning for Tactical Resource Control and Subsequent Maneuver Generation
  2026/2/1
• LACY: A Vision-Language Model-based Language-Action Cycle for Self-Improving Robotic Manipulation
  2025/11/1
• Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models
  2025/10/1
• Attribute-based Object Grounding and Robot Grasp Detection with Spatial Reasoning
  2025/9/1
• Optimal Robotic Velcro Peeling with Force Feedback
  2025/6/1
• Attribute-Based Robotic Grasping with Data-Efficient Adaptation
  2025/1/1
• Learning for Deformable Linear Object Insertion Leveraging Flexibility Estimation from Visual Cues
  2024/10/1
• A Parameter-Efficient Tuning Framework for Language-guided Object Grounding and Robot Grasping
  2024/9/1
• SlotGNN: Unsupervised Discovery of Multi-Object Representations and Visual Dynamics
  2023/10/1
• Adversarial Object Rearrangement in Constrained Environments with Heterogeneous Graph Neural Networks
  2023/9/1
• IOSG: Image-driven Object Searching and Grasping
  2023/8/1
• Active Mass Distribution Estimation from Tactile Feedback
  2023/3/1
• Self-Supervised Interactive Object Segmentation Through a Singulation-and-Grasping Approach
  2022/7/1
• Interactive Robotic Grasping with Attribute-Guided Disambiguation
  2022/3/1
• Learning Object Relations with Graph Neural Networks for Target-Driven Grasping in Dense Clutter
  2022/3/1
• KINet: Unsupervised Forward Models for Robotic Pushing Manipulation
  2022/2/1
• Attribute-Based Robotic Grasping with One-Grasp Adaptation
  2021/4/1
• Collision-Aware Target-Driven Object Grasping in Constrained Environments
  2021/4/1
• Learning to Generate 6-DoF Grasp Poses with Reachability Awareness
  2019/10/1
• Learning Visual Affordances with Target-Orientated Deep Q-Network to Grasp Objects by Harnessing Environmental Fixtures
  2019/10/1
• A Deep Learning Approach to Grasping the Invisible
  2019/9/1