Optimal planning of robot calibration experiments by genetic algorithms

Corresponding Author

Hanqi Zhuang

Department of Electrical Engineering, Florida Atlantic University, Boca Raton, FL 33431

Department of Electrical Engineering, Florida Atlantic University, Boca Raton, FL 33431Search for more papers by this author

Jie Wu,

Jie Wu

Department of Computer Science and Engineering, Florida Atlantic University, Boca Raton, FL 33431

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Weizhen Huang,

Weizhen Huang

Stromberg-Carlson Telecommunication, Siemens, Boca Raton, FL 33431

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Hanqi Zhuang,

Corresponding Author

Hanqi Zhuang

Department of Electrical Engineering, Florida Atlantic University, Boca Raton, FL 33431

Department of Electrical Engineering, Florida Atlantic University, Boca Raton, FL 33431Search for more papers by this author

Jie Wu,

Jie Wu

Department of Computer Science and Engineering, Florida Atlantic University, Boca Raton, FL 33431

Search for more papers by this author

Weizhen Huang,

Weizhen Huang

Stromberg-Carlson Telecommunication, Siemens, Boca Raton, FL 33431

Search for more papers by this author

First published: 07 December 1998

https://doi.org/10.1002/(SICI)1097-4563(199710)14:10<741::AID-ROB4>3.0.CO;2-U

Citations: 15

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Abstract

In this article, techniques developed in the science of genetic computing are applied to solve the problem of optimally selecting robot measurement configurations, which is an important element in successfully completing a robot calibration experiment. Genetic algorithms are customized for a type of robot measurement configuration selection problem in which the robot workspace constraints are defined in terms of robot joint limits. Simulation studies are conducted to examine the effectiveness of the genetic algorithms for the application. ©1997 John Wiley & Sons, Inc.

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Volume14, Issue10

October 1997

Pages 741-752

Optimal planning of robot calibration experiments by genetic algorithms

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