11 papers
RadLoc: Radar-based 3-DoF Global Localization via Fast, Robust, and Lightweight Spatial Descriptor Across Diverse Environmental Scenarios
Hogyun Kim, Jiwon Choi, Jungwoo Lee +1
While global localization using spinning radar has gained attention for its robustness to adverse weather and challenging environments, many studies have focused on individual comp…
Robust Image Processing Techniques for Construction Environment Monitoring Using Underwater Robots
Seunghee Yun, Geonmo Yang, Juhui Lee +3
This paper proposes a robust image processing framework for underwater robot-based construction environment monitoring, targeting complex degradations observed in real marine envir…
KISS-IMU: Self-supervised Inertial Odometry with Motion-balanced Learning and Uncertainty-aware Inference
Jiwon Choi, Hogyun Kim, Geonmo Yang +2
Inertial measurement units (IMUs), which provide high-frequency linear acceleration and angular velocity measurements, serve as fundamental sensing modalities in robotic systems. R…
Commerge: Communication-Efficient, Robust, and Fast LiDAR Map Merging Framework for Multi-Robot Coordination in Resource-Constrained Scenarios
Hogyun Kim, Jiwon Choi, Juwon Kim +4
By maintaining global consistency across robot teams, multi-robot LiDAR map merging enables faster exploration and efficient area coverage. However, map merging requires exchanging…
SKiD-SLAM: Robust, Lightweight, and Distributed Multi-Robot LiDAR SLAM in Resource-Constrained Field Environments
Hogyun Kim, Jiwon Choi, Juwon Kim +4
Distributed LiDAR SLAM is crucial for achieving efficient robot autonomy and improving the scalability of mapping. However, two issues need to be considered when applying it in fie…
Uni-Mapper: Unified Mapping Framework for Multi-modal LiDARs in Complex and Dynamic Environments
Gilhwan Kang, Hogyun Kim, Byunghee Choi +3
The unification of disparate maps is crucial for enabling scalable robot operation across multiple sessions and collaborative multi-robot scenarios. However, achieving a unified ma…