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Namsun Son

dblp:117/2181 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

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 · 50% Planning, search and constraint satisfaction · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › pathfinding › grid-based pathfinding
any-angle path planning
0.112012
Any-angle path planning with limit-cycle circle set for marine surface vehicle · ICRA 2012
Robotics › Motion planning and robot control
motion planning
0.112012
Any-angle path planning with limit-cycle circle set for marine surface vehicle · ICRA 2012

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

occupancy grid map · 0.1limit-cycle circle set · 0.1
YearPublicationVenuePosition
2012 Any-angle path planning with limit-cycle circle set for marine surface vehicle
abstract
Most path planning algorithms for a marine surface vehicle in the ocean environment have been developed only for a 2-D (x;y) plane without considering the vehicle heading angle. As a result, the vehicle has a difficulty in following the path correctly. In this paper, we propose a limit-cycle circle set that applies to the Theta* algorithm. The minimum turning radius of a marine surface vehicle is calculated using a limit-cycle circle set, and circles of this radius is used to generate a configuration space of an occupancy grid map. After applying Theta* to this configuration space, the limit-cycle circle set is also applied to the start and end nodes to find the appropriate path with specified heading angles. The benefit of this algorithm is its fast computation time compared to other 3-D (x;y;θ) path planning algorithms, along with the fact that it can be applied to the 3-D kinematic state of the vehicle. We simulate the proposed algorithm and compare it with 3-D A* and 3-D A* with post smoothing algorithms.
Hanguen Kim, Taehwan Lee, Hyun Chung, Namsun Son, Hyun Myung
ICRA4