Demo Data from EDBT 2026 / reviewers in the wild / expert
Won Suk You
dblp:22/8365
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2010
0000-0002-1118-9422ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Robot navigation and mapping · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping › localization
global localization |
0.1 | 1 | 2010 | Global localization for a small mobile robot using magnetic patterns · ICRA 2010 |
Robotics › Robot navigation and mapping
localization |
0.1 | 1 | 2010 | Global localization for a small mobile robot using magnetic patterns · ICRA 2010 |
Robotics › Robot navigation and mapping › environment mapping
landmark-based mapping |
0.0 | 1 | 2010 | Global localization for a small mobile robot using magnetic patterns · ICRA 2010 |
Methods — techniques the papers use, named apart from their topics
heuristic pattern search · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Global localization for a small mobile robot using magnetic patternsabstractIn this paper, we present a global localization and local pose error compensation method in a known structured environment using magnetic landmarks. In previous our research, it was possible to compensate the pose error (xe, ye, qe) of a mobile robot correctly on the surface of structured environment with magnetic landmarks. In this work, we propose a methodology of arranging magnetic landmarks on the map such that properly arranged magnetic patterns ease the global localization of a mobile agent. Among total six patterns of magnetic-bar in square arrangement, five unique landmarks are obtained. Therefore, a heuristic pattern search method is applied to build the virtual map using five landmarks. In order to obtain the global pose information, the robot identifies the pattern of magnets, and obtains the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. Experimental results show the effectiveness of the magnetic-pattern landmarks for the global localization and local pose control of a mobile robot. Won Suk You, Byungjune Choi, Hyungpil Moon, Jachoon Koo, Wan Kyun Chung, Hyoukryeol Choi |
ICRA | 1 |