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Seokgyu Kim

dblp:33/6434 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2007
—ORCID · none

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
Motion planning and robot control · 61% Robot navigation and mapping · 39%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
path planning
0.112007
Safe navigation of a mobile robot using the visibility information · ICRA 2007
Robotics › Robot navigation and mapping › mobile robot navigation
safe navigation
0.112007
Safe navigation of a mobile robot using the visibility information · ICRA 2007
Robotics › Motion planning and robot control › robot control › motion control
speed control
0.112007
Safe navigation of a mobile robot using the visibility information · ICRA 2007

Methods — techniques the papers use, named apart from their topics

visibility information · 0.1hybrid control · 0.1
YearPublicationVenuePosition
2007 Safe navigation of a mobile robot using the visibility information
abstract
In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "invisible" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.
Seokgyu Kim, Woojin Chung, Chang-Bae Moon, Jae-Bok Song
ICRA1