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Hierarchical and Modular Network on Non-prehensile Manipulation in General Environments
Yoonyoung Cho, Junhyek Han, Jisu Han, Beomjoon Kim
Robotics: Science and Systems (RSS), 2025
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Adaptive visual abstraction via object token merging and pruning for efficient robot manipulation
Jisu Han
CVPR Workshop (Causal and Object-Centric Representations for Robotics) 2024 Oral
[Paper][Github]
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Preference learning for guiding the tree search in continuous POMDPs
Jiyong Ahn, Sanghyeon Son, Dongryung Lee, Jisu Han, Dongwon Son, and Beomjoon Kim.
Conference on Robot Learnining (CoRL), 2023.
[Paper][Video][Project][Github]
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Hybrid-Space Diffusion for Task and Motion Planning with Offline RL
Jisu Han, Yoonyoung Cho, and Haewon Jung (AI707: Advanced Topics in Deep Learning (Prof. Kimin Lee) Class project)
TL;DR To resolve the downward refinement issues from bi-level planning in Task and Motion planning (TAMP), we adopt
hybrid-space diffusion model.
[Project]
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Clarifying the task: Identifying task from human videos as a representation
Jisu Han and Doohyun Lee (AI611: Machine Learning for Robotics (Prof. Joseph Lim) Class project)
TL;DR To learn a generalized reward function that can be utilized on reinforcement learning, we devise a representation that can effectively disentangle environment information and task information.
[Project]
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Compositional Meta Reinforcement Learning
Yoonyoung Cho and Jisu Han (AI614: Advanced deep learning (Prof. Sungju Hwang) Class project)
TL;DR We inject compositional reasoning for robots to quickly learn novel tasks by leveraging reusable elements from previous experiments.
[Paper]
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