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Y. P. Cheung

dblp:126/4921 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1996
—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 · 67% Planning, search and constraint satisfaction · 33%

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

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › intelligent control
fuzzy control
0.011996
Fuzzy-logic control for differential-wheel-drive AGVs using linear opto-sensor arrays · ICRA 1996
Robotics › Motion planning and robot control › robot control
output feedback control
0.011996
Fuzzy-logic control for differential-wheel-drive AGVs using linear opto-sensor arrays · ICRA 1996
Robotics › Motion planning and robot control
path following
0.011996
Fuzzy-logic control for differential-wheel-drive AGVs using linear opto-sensor arrays · ICRA 1996

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

popov criterion · 0.0linear control · 0.0hurwitz criterion · 0.0fuzzy logic · 0.0
YearPublicationVenuePosition
1996 Fuzzy-logic control for differential-wheel-drive AGVs using linear opto-sensor arrays
abstract
The performance of automatic guided vehicles (AGVs) is gauged by their position and orientation errors. Sometimes the orientation errors are not measurable, and output feedback using position errors only is employed. In this paper, a controller using output feedback is proposed for a differential-wheel-drive AGV with a simple linear array of 64/spl times/1 opto-sensors. A linear controller is first developed. The performance of the linear controller is further improved using fuzzy logic. Two fuzzy-logic controllers are accordingly formed. Stability based on the Hurwitz criterion, the Popov criterion, and the phase-plane method is demonstrated. Experimental results using a laboratory AGV are provided to illustrate the effectiveness of the proposed controllers.
Shiu Kit Tso, Y. H. Fung, Y. P. Cheung
ICRA3