Abstract

Precise online ending supervision for target positioning plays an important role in inertial confinement fusion (ICF) experiments. This paper presents a 6 degree of freedom (6DOF) ICF target displacement and rotation detection method using a scale invariant feature transform (SIFT) algorithm. A SIFT algorithm can extract image key points, which are localized to subpixel accuracy and can perform reliable matching between different views of an object. For testing the accuracy offline, precise and known displacement was given by an electromotor on a calibrated optical grating-vision platform. When the platform moves along its x axis, the image of each step is captured with corresponding grating sensor values recorded. Offline experimental results prove that the different values between the image points and grating sensor are less than 1 μm (1/10 pixel). In online conditions, a 6DOF parallel robot subsystem is used as an ending driver, and a target alignment sensor is used to capture four orthogonal images. The feedback information is obtained by SIFT features. Due to the excellent matching ability and 1/10 subpixel localization accuracy of the SITF features, the proposed method can accurately and reliably online detect the displacement and rotation of target. The experimental results demonstrate the effectiveness of the method.

© 2015 Optical Society of America

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