Jae-Ho Kim (SAMPLE)
Director, Professor
SLAM · Reinforcement Learning
SLAM
3D Perception & Localization
SAMPLE TEXT. We study simultaneous localization and mapping for robots that operate in cluttered, changing environments. Our work covers sensor fusion, loop closure under perceptual aliasing, and maps that carry semantic meaning rather than geometry alone.
Team
Jiwon Kang (SAMPLE)
Ph.D. Student
SLAM
Publications
View All[SAMPLE] Learning-Based Visual Navigation for Dynamic Indoor Environments
ICRA 2026 — IEEE International Conference on Robotics and Automation
Best Paper Award Finalist
[SAMPLE] Semantic Mapping with Uncertainty-Aware Sensor Fusion
T-RO 2026 — IEEE Transactions on Robotics
[SAMPLE] Robust SLAM with Learned Deep Features
RA-L 2024 — IEEE Robotics and Automation Letters
Best Paper Award (SAMPLE)
[SAMPLE] Sensor Fusion Module for Mobile Robot Localization
KR Patent 2023 — Republic of Korea Patent Office
News
View All
[SAMPLE] New Paper Published in IEEE T-RO
Our work on semantic mapping for long-term robot autonomy has been published.
[SAMPLE] Best Paper Award Finalist at ICRA 2026
Our paper on learning-based visual navigation was selected as a Best Paper Award finalist.
[SAMPLE] IRL-CBNU at ICRA 2025
Members of the laboratory presented two papers at ICRA 2025.