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Laser-based geometrical modeling of large-scale architectural structures using co-operative multiple robots

Laser-based geometrical modeling of large-scale architectural structures using co-operative... For the construction of 3-D shape models of large-scale architectural structures using laser range finders, a number of range images are taken from different viewpoints around the targets. Next, the obtained images are normally aligned by post-processing procedures, such as the ICP algorithm. However, to obtain convergent results in the ICP algorithm and align these range images to their proper positions, the initial position of each range image needs to be manually aligned to roughly the correct position. This paper proposes a new measurement and modeling system using a group of multiple robots and an on-board laser range finder. Each measurement position is identified by a highly precise positioning technique called the Co-operative Positioning System (CPS), which utilizes the characteristics of the multiple-robot system. Therefore, the proposed system can construct 3-D shapes of large-scale architectural structures without any post-processing procedure or manual intervention. In addition, it is possible to register range images even if the number of measurements is few and there are only a few range images, for example, due to range images containing insufficient feature shapes or overlapping regions. Measurement experiments in unknown and large indoor/outdoor environments including a large hall, a building, an urban district, and a cultural heritage have been successfully carried out using the newly developed measurement system consisting of three mobile robots named CPS-V. Path generation experiments of the mobile robots based on the partially measured 3-D model are also presented. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Autonomous Robots Springer Journals

Laser-based geometrical modeling of large-scale architectural structures using co-operative multiple robots

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References (32)

Publisher
Springer Journals
Copyright
Copyright © 2011 by Springer Science+Business Media, LLC
Subject
Engineering; Artificial Intelligence (incl. Robotics); Computer Imaging, Vision, Pattern Recognition and Graphics; Control, Robotics, Mechatronics; Robotics and Automation
ISSN
0929-5593
eISSN
1573-7527
DOI
10.1007/s10514-011-9256-x
Publisher site
See Article on Publisher Site

Abstract

For the construction of 3-D shape models of large-scale architectural structures using laser range finders, a number of range images are taken from different viewpoints around the targets. Next, the obtained images are normally aligned by post-processing procedures, such as the ICP algorithm. However, to obtain convergent results in the ICP algorithm and align these range images to their proper positions, the initial position of each range image needs to be manually aligned to roughly the correct position. This paper proposes a new measurement and modeling system using a group of multiple robots and an on-board laser range finder. Each measurement position is identified by a highly precise positioning technique called the Co-operative Positioning System (CPS), which utilizes the characteristics of the multiple-robot system. Therefore, the proposed system can construct 3-D shapes of large-scale architectural structures without any post-processing procedure or manual intervention. In addition, it is possible to register range images even if the number of measurements is few and there are only a few range images, for example, due to range images containing insufficient feature shapes or overlapping regions. Measurement experiments in unknown and large indoor/outdoor environments including a large hall, a building, an urban district, and a cultural heritage have been successfully carried out using the newly developed measurement system consisting of three mobile robots named CPS-V. Path generation experiments of the mobile robots based on the partially measured 3-D model are also presented.

Journal

Autonomous RobotsSpringer Journals

Published: Sep 23, 2011

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