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Dong-Ming Chuang

dblp:34/8144 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1997
—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 · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › sensor-based control › visual servoing
image-based visual servoing
0.011997
Adaptive fuzzy visual servoing in robot control · ICRA 1997
Robotics › Motion planning and robot control
robot control
0.011997
Adaptive fuzzy visual servoing in robot control · ICRA 1997
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.011997
Adaptive fuzzy visual servoing in robot control · ICRA 1997
Robotics › Motion planning and robot control › robot control › adaptive control
robust adaptive control
0.011997
Adaptive fuzzy visual servoing in robot control · ICRA 1997

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

fuzzy estimator · 0.0adaptive robust control · 0.0
YearPublicationVenuePosition
1997 Adaptive fuzzy visual servoing in robot control
abstract
We address the problem of controlling a robot to track a randomly moved object using visual servoing techniques. A new visual servo mechanism, based on the image-based servoing principle, is proposed in this study. A fuzzy estimator is used to estimate the relationship between perspective projection and the kinematics and an adaptive robust controller is used to compensate the tracking error induced by the estimator and the tracking error caused by the robot's parameter uncertainties. Using this method, the extrinsic calibration between the robot system and the camera system can be eliminated. The proposed controller not only guarantees the global stability of the visual servoing system but also drives the target error to a neighborhood of zero. Simulation results are presented which show the performance of the proposed controller works well.
Dong-Ming Chuang, Shiaw-Chian Wu, Maw-kae Hor
ICRA1