Application of genetic programming to the calibration of industrial robots

Robot calibration is a widely studied area for which a variety of solutions have been generated. Most of the methods proposed address the calibration problem by establishing a model structure followed by indirect, often ill-conditioned numeric parameter identification. This paper introduces a new in...

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Bibliographic Details
Published in:Computers in industry 2007-04, Vol.58 (3), p.255-264
Main Authors: Dolinsky, J.U., Jenkinson, I.D., Colquhoun, G.J.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Co-evolution
Computer science
control theory
systems
Control theory. Systems
Distal supervised learning
Exact sciences and technology
Inverse static kinematic calibration
Process control. Computer integrated manufacturing
Robotics
Software
Software engineering
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Summary:Robot calibration is a widely studied area for which a variety of solutions have been generated. Most of the methods proposed address the calibration problem by establishing a model structure followed by indirect, often ill-conditioned numeric parameter identification. This paper introduces a new inverse static kinematic calibration technique based on genetic programming, which is used to establish and identify model structure and parameters. The technique has the potential to identify the true calibration model avoiding the problems of conventional methods. The fundamentals of this approach are described and experimental results provided.
ISSN:0166-3615
1872-6194
DOI:10.1016/j.compind.2006.06.003