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B. Preising

dblp:153/6604 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1991
—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 · 44% Trustworthy machine learning · 28% 3D vision · 28%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Trustworthy machine learning
calibration
0.011991
Robot performance measurement and calibration using a 3D computer vision system · ICRA 1991
Robotics › Motion planning and robot control
robot calibration
0.011991
Robot performance measurement and calibration using a 3D computer vision system · ICRA 1991
Computer vision › 3D vision
vision-based measurement
0.011991
Robot performance measurement and calibration using a 3D computer vision system · ICRA 1991
Robotics › Motion planning and robot control
robot control
0.011991
Robot performance measurement and calibration using a 3D computer vision system · ICRA 1991
Robotics › Motion planning and robot control › robot control › sensor-based control
vision-based control
0.011991
Robot performance measurement and calibration using a 3D computer vision system · ICRA 1991

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

vision feedback · 0.0kinematic equations · 0.0
YearPublicationVenuePosition
1991 Robot performance measurement and calibration using a 3D computer vision system
abstract
The use of a single-camera 3D computer vision system as a position sensor in order to perform robot calibration is examined. A vision feedback scheme, termed vision-guided robot control (VRC), that can improve the accuracy of a robot in an online iterative manner is described. This system demonstrates the advantage that can be achieved by a Cartesian space robot control scheme when end-effector position and orientation are actually sensed instead of calculated from the kinematic equations. The viability of using a vision system for robot calibration is demonstrated by experimentally showing that the accuracy of a robot can be drastically improved. The vision system can also be used to determine the repeatability and accuracy of a robot in a simple, efficient, and quick manner. Experimental work with an IBM electric drive robot and the proposed vision system produced a 97- and 145-fold improvement in the position and orientation accuracy of the robot, respectively.>
B. Preising, Tien C. Hsia
ICRA1