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Shui H. Motaghedi

dblp:63/6890 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1999
—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% Robot navigation and mapping · 33%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot calibration
kinematic parameter identification
0.011999
Robot Calibration with Planar Constraints · ICRA 1999
Robotics › Robot navigation and mapping › state estimation
observability analysis
0.011999
Robot Calibration with Planar Constraints · ICRA 1999
Robotics › Motion planning and robot control
robot calibration
0.011999
Robot Calibration with Planar Constraints · ICRA 1999

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

simulation · 0.0planar constraints · 0.0
YearPublicationVenuePosition
1999 Robot Calibration with Planar Constraints
abstract
Investigates robot calibration with planar constraints, and in particular the conditions for the parameters of the robot kinematic model to be observable. Mainly multiple-plane constraints for robot calibration are considered. It is first shown that a single-plane constraint is normally not sufficient to calibrate a robot. It is also proven that by using a three-plane constraint, the constrained system is equivalent to an unconstrained point-measurement system under certain conditions. The significance of this observation is that one can use the three-plane constraint setup to successfully calibrate a robot. Simulations have been conducted to verify the theory presented in the paper.
Hanqi Zhuang, Shui H. Motaghedi, Zvi S. Roth
ICRA2