4 papers
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…
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…
MARSCalib: Multi-robot, Automatic, Robust, Spherical Target-based Extrinsic Calibration in Field and Extraterrestrial Environments
Seokhwan Jeong, Hogyun Kim, Younggun Cho
This paper presents a novel spherical target-based LiDAR-camera extrinsic calibration method designed for outdoor environments with multi-robot systems, considering both target and…
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…