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Haptically enabled simulation system for firearm shooting training
journal contribution
posted on 2019-09-01, 00:00 authored by Lei WeiLei Wei, Hailing Zhou, Saeid NahavandiFirearm shooting training is of importance in military and law enforcement training tasks. Traditional training usually uses actual firearms or modified bullets that are dangerous and expensive and difficult to evaluate the performance. Firearm training simulation systems provide risk-free alternatives. However, most existing simulation is visual-only, which lacks the immersion on the force feedback. In this paper, we proposed a new firearm training simulation system, which can provide more realistic training by incorporating physic effects on recoil and trigger pull weight. Dynamic, immersive, and repeatable training experiences while imposes no danger to trainees are provided in our system. The system consists of haptics, physics engine, and motion capture. These three components are carefully combined by developing the corresponding techniques of haptic force rendering, visuo-haptic integration, and synchronisation, physics-based dynamic simulation and motion analysis. Compared with existing systems, our training system has more complete functionalities that include visual firearm shooting, force generation, shooting reactions, result analysis and evaluation. Moreover, it is adaptable to off-the-shelf hardware and software packages and thus it can provide flexibility to system scalability and budget. To evaluate the proposed system, two demonstrations are conducted for users where the systems accuracy, immersion and usability are analysed. The results show the effectiveness of our physics-based shooting model and the proposed system on simulating different shooting scenarios.
History
Journal
Virtual realityVolume
3Issue
217Season
228Pagination
217 - 228Publisher
SpringerLocation
London, Eng.Publisher DOI
ISSN
1359-4338eISSN
1434-9957Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2018, Springer-Verlag London Ltd., part of Springer NatureUsage metrics
Keywords
Virtual training simulationHapticsPhysics engineMotion captureScience & TechnologyTechnologyComputer Science, Interdisciplinary ApplicationsComputer Science, Software EngineeringImaging Science & Photographic TechnologyComputer ScienceVIRTUAL-REALITYKINECTArtificial Intelligence and Image Processing
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