Comparison of pose error compensation for focal plane pose test platform using GRNN and CART

Qiang Lu; Jianping Wang; Feifan Zhang; Zengxiang Zhou

doi:10.1117/12.2311790

10 July 2018 Comparison of pose error compensation for focal plane pose test platform using GRNN and CART

Qiang Lu, Jianping Wang, Feifan Zhang, Zengxiang Zhou

Proceedings Volume 10706, Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation III; 107062S (2018) https://doi.org/10.1117/12.2311790
Event: SPIE Astronomical Telescopes + Instrumentation, 2018, Austin, Texas, United States

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.

Citation Download Citation

Qiang Lu, Jianping Wang, Feifan Zhang, and Zengxiang Zhou "Comparison of pose error compensation for focal plane pose test platform using GRNN and CART", Proc. SPIE 10706, Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation III, 107062S (10 July 2018); https://doi.org/10.1117/12.2311790

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available