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Symmetry 2017, 9(4), 55;

3D Reconstruction Framework for Multiple Remote Robots on Cloud System

Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Korea
Department of Computer and Information Science, University of Macau, Avenida da Universidade, Taipa, Macau SAR 3000, China
Institute of Defense Advanced Technology Research, Agency for Defense Development, P.O. Box 35, Yuseong, Daejeon 34186, Korea
Author to whom correspondence should be addressed.
Academic Editors: Doo-Soon Park and Shu-Ching Chen
Received: 13 December 2016 / Revised: 7 April 2017 / Accepted: 7 April 2017 / Published: 14 April 2017
(This article belongs to the Special Issue Scientific Programming in Practical Symmetric Big Data)
Full-Text   |   PDF [4222 KB, uploaded 14 April 2017]   |  


This paper proposes a cloud-based framework that optimizes the three-dimensional (3D) reconstruction of multiple types of sensor data captured from multiple remote robots. A working environment using multiple remote robots requires massive amounts of data processing in real-time, which cannot be achieved using a single computer. In the proposed framework, reconstruction is carried out in cloud-based servers via distributed data processing. Consequently, users do not need to consider computing resources even when utilizing multiple remote robots. The sensors’ bulk data are transferred to a master server that divides the data and allocates the processing to a set of slave servers. Thus, the segmentation and reconstruction tasks are implemented in the slave servers. The reconstructed 3D space is created by fusing all the results in a visualization server, and the results are saved in a database that users can access and visualize in real-time. The results of the experiments conducted verify that the proposed system is capable of providing real-time 3D scenes of the surroundings of remote robots. View Full-Text
Keywords: 3D reconstruction; ground segmentation; cloud system; point cloud 3D reconstruction; ground segmentation; cloud system; point cloud

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Chu, P.M.; Cho, S.; Fong, S.; Park, Y.W.; Cho, K. 3D Reconstruction Framework for Multiple Remote Robots on Cloud System. Symmetry 2017, 9, 55.

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