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Shinwoo Kang

dblp:139/2918 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2004
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 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
Legged, aerial and field robots · 87% Motion planning and robot control · 13%

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

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
field robotics
0.012004
Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers · IEEE Trans. Robotics 2004
Robotics › Legged, aerial and field robots › field robotics
planetary rover
0.012004
Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers · IEEE Trans. Robotics 2004
Robotics › Motion planning and robot control › mobile robot control
traction control
0.012004
Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers · IEEE Trans. Robotics 2004

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

terramechanics equations · 0.0linear least squares · 0.0
YearPublicationVenuePosition
2004 Online terrain parameter estimation for wheeled mobile robots with application to planetary rovers
abstract
Future planetary exploration missions will require wheeled mobile robots ("rovers") to traverse very rough terrain with limited human supervision. Wheel-terrain interaction plays a critical role in rough-terrain mobility. In this paper, an online estimation method that identifies key terrain parameters using on-board robot sensors is presented. These parameters can be used for traversability prediction or in a traction control algorithm to improve robot mobility and to plan safe action plans for autonomous systems. Terrain parameters are also valuable indicators of planetary surface soil composition. The algorithm relies on a simplified form of classical terramechanics equations and uses a linear-least squares method to compute terrain parameters in real time. Simulation and experimental results show that the terrain estimation algorithm can accurately and efficiently identify key terrain parameters for various soil types.
Karl Iagnemma, Shinwoo Kang, Hassan Shibly, Steven Dubowsky
IEEE Trans. Robotics2