Cited 13 time in
3D Reconstruction Framework for Multiple Remote Robots on Cloud System
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Chu, Phuong Minh | - |
| dc.contributor.author | Cho, Seoungjae | - |
| dc.contributor.author | Fong, Simon | - |
| dc.contributor.author | Park, Yong Woon | - |
| dc.contributor.author | Cho, Kyungeun | - |
| dc.date.accessioned | 2024-09-26T19:31:40Z | - |
| dc.date.available | 2024-09-26T19:31:40Z | - |
| dc.date.issued | 2017-04 | - |
| dc.identifier.issn | 2073-8994 | - |
| dc.identifier.issn | 2073-8994 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/26131 | - |
| dc.description.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. | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | MDPI | - |
| dc.title | 3D Reconstruction Framework for Multiple Remote Robots on Cloud System | - |
| dc.type | Article | - |
| dc.publisher.location | 스위스 | - |
| dc.identifier.doi | 10.3390/sym9040055 | - |
| dc.identifier.scopusid | 2-s2.0-85018674007 | - |
| dc.identifier.wosid | 000401810100009 | - |
| dc.identifier.bibliographicCitation | SYMMETRY-BASEL, v.9, no.4 | - |
| dc.citation.title | SYMMETRY-BASEL | - |
| dc.citation.volume | 9 | - |
| dc.citation.number | 4 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
| dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
| dc.subject.keywordPlus | HUMAN ACTIVITY RECOGNITION | - |
| dc.subject.keywordPlus | REAL-TIME | - |
| dc.subject.keywordPlus | TRACKING | - |
| dc.subject.keywordPlus | FEATURES | - |
| dc.subject.keywordPlus | PULSES | - |
| dc.subject.keywordPlus | CARE | - |
| dc.subject.keywordAuthor | 3D reconstruction | - |
| dc.subject.keywordAuthor | ground segmentation | - |
| dc.subject.keywordAuthor | cloud system | - |
| dc.subject.keywordAuthor | point cloud | - |
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