Autonomous metrology for robot mounted 3D vision systems

被引：10

作者：

Kinnell, Peter ^{[1
]}

Rymer, Tom ^{[1
]}

Hodgson, John ^{[1
]}

Justham, Laura ^{[1
]}

Jackson, Mike ^{[1
]}

机构：

[1] Loughborough Univ, EPSRC Ctr Innovat Mfg Intelligent Automat, Loughborough, Leics, England

来源：

CIRP ANNALS-MANUFACTURING TECHNOLOGY | 2017年 / 66卷 / 01期

基金：

英国工程与自然科学研究理事会;

关键词：

Metrology; Cognitive robotics; 3D image processing;

D O I：

10.1016/j.cirp.2017.04.069

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Using a metrology system simulation approach, an algorithm is presented to determine the best position for a robot mounted 3D vision system. Point cloud data is simulated, taking into account sensor performance, to create a ranked list of the best camera positions. These can be used by a robot to autonomously determine the most advantageous camera position for locating a target object. The algorithm is applied to an Ensenso active stereo 3D camera. Results show that when used in combination with a RANSAC object recognition algorithm, it increased positional precision by two orders of magnitude, from worst to best case. (C) 2017 Published by Elsevier Ltd on behalf of CIRP.

引用

页码：483 / 486

页数：4

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