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20242026
most citedNarrowing your FOV with SOLiD: Spatially Organized and Lightweight Global Descriptor for FOV-constrained LiDAR Place Recognition

33 citations · 49 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.RO2024

PoLaRIS Dataset: A Maritime Object Detection and Tracking Dataset in Pohang Canal

Jiwon Choi, Dongjin Cho, Gihyeon Lee +4

Maritime environments often present hazardous situations due to factors such as moving ships or buoys, which become obstacles under the influence of waves. In such challenging cond…

cs.RO2024★ 1 cited

DiTer++: Diverse Terrain and Multi-modal Dataset for Multi-Robot SLAM in Multi-session Environments

Juwon Kim, Hogyun Kim, Seokhwan Jeong +2

We encounter large-scale environments where both structured and unstructured spaces coexist, such as on campuses. In this environment, lighting conditions and dynamic objects chang…

cs.RO2024★ 33 cited

Narrowing your FOV with SOLiD: Spatially Organized and Lightweight Global Descriptor for FOV-constrained LiDAR Place Recognition

Hogyun Kim, Jiwon Choi, Taehu Sim +2

We often encounter limited FOV situations due to various factors such as sensor fusion or sensor mount in real-world robot navigation. However, the limited FOV interrupts the gener…

cs.RO2024★ 8 cited

ReFeree: Radar-Based Lightweight and Robust Localization using Feature and Free space

Hogyun Kim, Byunghee Choi, Euncheol Choi +1

Place recognition plays an important role in achieving robust long-term autonomy. Real-world robots face a wide range of weather conditions (e.g. overcast, heavy rain, and snowing)…

cs.RO2024★ 1 cited

ReFeree: Radar-based efficient global descriptor using a Feature and Free space for Place Recognition

Byunghee Choi, Hogyun Kim, Younggun Cho

Radar is highlighted for robust sensing capabilities in adverse weather conditions (e.g. dense fog, heavy rain, or snowfall). In addition, Radar can cover wide areas and penetrate…