Towards a Mixed Reality System for Construction Trade Training

Frédéric Bosché, Mohamed Samir Abdel-Wahab, Ludovico Carozza

Research output: Contribution to journalArticle

23 Citations (Scopus)
224 Downloads (Pure)

Abstract

Apprenticeship training is at the heart of government skills policy worldwide. Application of cutting edge Information and Communication Technologies (ICTs) can enhance the quality of construction training, and help in attracting youth to an industry that traditionally has a poor image and slow in up-taking innovation. We report on the development of a novel Mixed Reality (MR) system uniquely targeted for the training of construction trade workers, i.e. skilled manual workers. From a general training viewpoint, the system aims to address the shortcomings of existing construction trades training, in particular the lack of solutions for enabling trainees to train in realistic and challenging site conditions whilst eliminating Occupational Health and Safety risks. From a technical viewpoint, the system currently integrates state of the art Virtual Reality (VR) goggles with a novel cost-effective 6 degree-of-freedom (DOF) head pose tracking system supporting the movement of trainees in room-size spaces, as well as a game engine to effectively manage the generation of the views of the virtual 3D environment projected on the VR goggles. Experimental results demonstrate the performance of our 6-DOF head pose tracking system, which is the main computational contribution of the work presented here. Then, preliminary results reveal its value to enable trainees to experience construction site conditions, particularly being at height, in different settings. Details are provided regarding future work to extend the system into the envisioned full MR system whereby a trainee would be performing an actual task, e.g. bricklaying, whilst being immersed in a virtual project environment.
Original languageEnglish
Article number04015016
JournalJournal of Computing in Civil Engineering
Volume30
Issue number2
Early online date5 Mar 2015
DOIs
Publication statusPublished - Mar 2016

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