Real-time 3D Mine Modelling in the ¡VAMOS! Project

The project Viable Alternative Mine Operating System (¡VAMOS!) develops a new safe, clean and low visibility mining technique for excavating raw materials from submerged inland mines. During operations, the perception data of the mining vehicle can only be communicated to the operator via a computer...

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Bibliographic Details
Main Authors: Bleier, Michael, Dias, André, Ferreira, António, Pidgeon, John, Almeida, José, Silva, Eduardo, Schilling, Klaus, Nüchter, Andreas
Other Authors: TU Bergakademie Freiberg, Geowissenschaften, Geotechnik und Bergbau
Format: Others
Language:English
Published: Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola" 2018
Subjects:
Online Access:http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-231296
http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-231296
http://www.qucosa.de/fileadmin/data/qucosa/documents/23129/19.Real-time%203D%20Mine%20Modelling%20in%20the%20%C2%A1VAMOS%21_RTM2017-19_1b.pdf
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Summary:The project Viable Alternative Mine Operating System (¡VAMOS!) develops a new safe, clean and low visibility mining technique for excavating raw materials from submerged inland mines. During operations, the perception data of the mining vehicle can only be communicated to the operator via a computer interface. In order to assist remote control and facilitate assessing risks a detailed view of the mining process below the water surface is necessary. This paper presents approaches to real-time 3D reconstruction of the mining environment for immersive data visualisation in a virtual reality environment to provide advanced spatial awareness. From the raw survey data a more consistent 3D model is created using postprocessing techniques based on a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function (SDF) based mapping is employed to fuse the measurements from multiple views into a single representation and reduce sensor noise. Results of the proposed techniques are demonstrated on a dataset captured in an submerged inland mine.