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Won Suk You

dblp:22/8365 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping › localization
global localization
0.112010
Global localization for a small mobile robot using magnetic patterns · ICRA 2010
Robotics › Robot navigation and mapping
localization
0.112010
Global localization for a small mobile robot using magnetic patterns · ICRA 2010
Robotics › Robot navigation and mapping › environment mapping
landmark-based mapping
0.012010
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
YearPublicationVenuePosition
2010 Global localization for a small mobile robot using magnetic patterns
abstract
In 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
ICRA1