3D reconstruction framework for multiple remote robots on cloud system

Phuong Minh Chu, Seoungjae Cho, Simon Fong, Yong Woon Park, Kyungeun Cho

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

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.

Original languageEnglish
Article number55
JournalSymmetry
Volume9
Issue number4
DOIs
StatePublished - 1 Apr 2017

Keywords

  • 3D reconstruction
  • Cloud system
  • Ground segmentation
  • Point cloud

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