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News
- 12/2024: I passed my PhD Thesis Proposal!
- 10/2024: A new version of survey on foundation models and robotics was released! Check out here!
- 07/2024: My research work was featured in CMU School of Computer Science News.
- 11/2023: Attended CoRL 2023. Here are the notes on the sessions that I joined
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MapEx: Indoor Structure Exploration with Probabilistic Information Gain from Global Map Predictions
Cherie Ho*, Seungchan Kim*, Brady Moon, Aditya Parandekar, Narek Harutyunyan, Chen Wang, Katia Sycara, Graeme Best, Sebastian Scherer
(*: Equal Contributions)
arXiv preprint arXiv:2409.15590 (2024). Submitted to ICRA 2025
arXiv
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Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysis
Yafei Hu*, Quanting Xie*, Vidhi Jain*, Jonathan Francis, Jay Patrikar, Nikhil Keetha, Seungchan Kim, Yaqi Xie, Tianyi Zhang, Hao-Shu Fang, Shibo Zhao, Shayegan Omidshafiei, Dong-Ki Kim, Ali-akbar Agha-mohammadi, Katia Sycara, Matthew Johnson-Roberson, Dhruv Batra, Xiaolong Wang, Sebastian Scherer, Chen Wang, Zsolt Kira, Fei Xia, Yonatan Bisk
arXiv preprint arXiv:2312.08782 (2023).
project page | arXiv
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Multi-Robot Multi-Room Exploration with Geometric Cue Extraction and Circular Decomposition
Seungchan Kim, Micah Corah, John Keller, Graeme Best, Sebastian Scherer
IEEE Robotics and Automation Letters (RA-L) 2023
Presentation at International Conference on Robotics and Automation (ICRA) 2024
project page | arXiv | DOI | video | presentation video
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AirDet: Few-Shot Detection without Fine-tuning for Autonomous Exploration
Bowen Li, Chen Wang, Pranay Reddy, Seungchan Kim, Sebastian Scherer
European Conference on Computer Vision (ECCV) 2022
project page |
code |
arXiv |
DOI
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Robotic Interestingness via Human-Informed Few-Shot Object Detection
Seungchan Kim, Chen Wang, Bowen Li, Sebastian Scherer
IEEE/RSJ International Conference on Robotics and Systems (IROS) 2022
arXiv | DOI
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Unsupervised Online Learning for Robotic Interestingness with Visual Memory
Chen Wang, Yuheng Qiu, Wenshan Wang, Yafei Hu, Seungchan Kim, Sebastian Scherer
IEEE Transactions on Robotics (T-RO) 2021
project page | code | arXiv | DOI
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Using Computational Analysis of Behavior to Discover Developmental Change in Memory-Guided Attention Mechanisms in Childhood
Dima Amso, Lakshmi Govindarajan, Pankaj Gupta, Diego Placido, Heidi Baumgartner, Andrew Lynn, Kelley Gunther, Tarun Sharma, Vijay Veerabadran, Kalpit Thakkar, Seungchan Kim, Thomas Serre
PsyArXiv. doi:10.31234/osf.io/gq4rt
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Combating the Compounding-Error Problem with a Multi-step Model
Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michael Littman
arXiv preprint arXiv:1905.13320 (2019).
arXiv
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DeepMellow: Removing the Need for a Target Network in Deep Q-Learning
Seungchan Kim, Kavosh Asadi, Michael Littman, George Konidaris
International Joint Conference on Artificial Intelligence (IJCAI) 2019
Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) 2019
code | DOI
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Removing the Target Network from Deep Q-Networks with the Mellowmax Operator
Seungchan Kim, Kavosh Asadi, Michael Littman, George Konidaris
International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2019, Extended Abstract
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