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  4. Least squares orthogonal distance fitting of curves and surfaces in space
 
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2004
Doctoral Thesis
Title

Least squares orthogonal distance fitting of curves and surfaces in space

Abstract
This book presents in detail a complete set of best-fit algorithms for general curves and surfaces in space. Such best-fit algorithms approximate and estimate curve and surface parameters by minimizing the shortest distances between the vcurve of surface and the measurement point. After reviewing the basics for representing curves and surfaces in space and fitting in general, the author presents three algorithms for orthogonal distance fitting combining numerical methods and minimizational methods. These algorithms are applied to implicit and parametric curves and surfaces in 2D and 3D space possessing a broad variety of algorithmic features. Finally, an appendix provides practical information for applying the general orthogonal distance fitting algorithms to special model features. Obvious application areas of the algorithms presented are robot navigation, including the navigation of autonomous vehicles or the grasping of work pieces, as well as factory digitization in general.
Thesis Note
Zugl.: Stuttgart, Univ., Diss., 2004
Author(s)
Ahn, S.J.
Publisher
Springer  
Publishing Place
Berlin
Language
English
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA  
Keyword(s)
  • curve fitting

  • Surface Fitting

  • geometric distance

  • Geometrische Meßtechnik

  • Orthogonal Distance Fitting

  • parameter spaces

  • Nonlinear Least Squares

  • Punktwolke

  • point cloud

  • Messen geometrischer Größen

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