Landmine detection training simulation using virtual reality technology

Merve Varol Arısoy

doi:10.1007/s10055-020-00467-1

Return

Landmine detection training simulation using virtual reality technology

2020-08-31

PRE

Merve Varol Arısoy *

DOI：10.1007/s10055-020-00467-1

Original

Original request for help

Save

Abstract

En 中文

Landmines are frequently used for defence and attack. Thus, landmine detection is vital to preventing the damages incurred. Various landmine detection methods have been developed from the past to the present. Thus, a need has arisen for the employment of qualified personnel in this field. In today's landmine detection training, soldiers are first subjected to theoretical training about landmine types. After this stage, they attend practical training in the field. However, when training is given in this way, sample application fields do not contain all possible terrain and weather conditions. Also, many accidents and injuries occur during this practical training. To overcome the disadvantages elucidated above, a landmine detection training simulation was developed in this study, which supports real terrain conditions and creates a safe detection environment. In this study, the developed simulation software was based on virtual reality technology. The interaction with the computer is both provided by a detector appearance control device (DACD) controller developed for this simulator and by Kinect controller. The simulator has remarkable benefits concerning time and cost when compared with the landmine detection training given today. At the same time, detections performed in a safe environment without any risk factors and real land conditions were provided close to reality. Also, the actual space coordinates of the joints in the human body can be detected correctly using the DACD controller, as much as the Kinect device.

Keywords:

Landmine detection training

Simulation

Unity 3D

Landmine sweeping

Kinect V2

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.