Counter-mine augmented reality training system (CMARTS)

Tana Maurer; Kenneth Cook; John Graybeal

doi:10.1117/12.2518120

10 May 2019 Counter-mine augmented reality training system (CMARTS)

Tana Maurer, Kenneth Cook, John Graybeal

Author Affiliations +

Proceedings Volume 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV; 1101210 (2019) https://doi.org/10.1117/12.2518120
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Advances in training and simulation technologies, particularly in the arena of augmented reality systems, not only enable a more immersive training experience for users, but also provide more opportunities to execute training both within and outside of operational environments. The Counter-Mine Augmented Reality Training System (CMARTS) effort was an investigation of fusion of augmented reality and embedded training capabilities into fielded hand-held mine detectors to support performance training at home stations, as well as in operational environments. The resulting system, including both metal detection and ground penetrating radar (GPR) sensors, provides: (1) real-time operator feedback in the form of augmented visualizations and (2) embedded “anywhere-anytime” mine detection training using simulated targets. The real-time feedback consists of a head-mounted display and tablet visualizations to indicate what areas of ground have already been scanned; markers for where devices have already been located; any problems with user swing; detector height and swing speed; and also device power status. The embedded training capability enables operators to practice mine detection in both indoor and outdoor environments with synthetic mines, to include actual device responses to simulated detection with real-time feedback. CMARTS will provide the basis for further investigation of augmented reality applications to support both real-time operations and training, not only for mine detection but for other sensing modalities and target types as well. This paper will start with a discussion of mine detection training challenges, followed by the design and development of CMARTS, concluding with possible future efforts.

Citation Download Citation

Tana Maurer, Kenneth Cook, and John Graybeal "Counter-mine augmented reality training system (CMARTS)", Proc. SPIE 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV, 1101210 (10 May 2019); https://doi.org/10.1117/12.2518120

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