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Comparison of pose error compensation for focal plane pose test platform using GRNN and CART
Author(s): Qiang Lu; Jianping Wang; Feifan Zhang; Zengxiang Zhou
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Paper Abstract

The surface accuracy of the telescope focal plate plays a key role in high-precision astronomical observations. The 6- DOF parallel Focal Plane Pose Test Platform (FPPTP) is used to measure the deformation and surface accuracy of the focal plate in different space pose, and precise pose adjustment is an important indicator of the platform's performance. But the factors affecting the pose error of the platform are complex and difficult to describe accurately with mathematical model. Comparison of pose error compensation for the focal plate in different space pose using Generalized Regression Neural Network (GRNN) and Classification Regression Tree (CART) is studied in this paper.

Paper Details

Date Published: 10 July 2018
PDF: 9 pages
Proc. SPIE 10706, Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation III, 107062S (10 July 2018); doi: 10.1117/12.2311790
Show Author Affiliations
Qiang Lu, Univ. of Science and Technology of China (China)
Jianping Wang, Univ. of Science and Technology of China (China)
Feifan Zhang, Univ. of Science and Technology of China (China)
Zengxiang Zhou, Univ. of Science and Technology of China (China)


Published in SPIE Proceedings Vol. 10706:
Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation III
Ramón Navarro; Roland Geyl, Editor(s)

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