VR Rules of the Road
Abstract
Navy warfighters need knowledge of the nautical rules of the road and related strong seamanship and ship-handling skills to reduce c"ollision risk and improve tactical warfighter performance. The development of a modern, easily distributable, standalone trainer for" teaching navigation rules of the road will provide strong tactical training built on a foundation of excellent seamanship. Our progress in developing such a standalone simulation trainer provides the opportunity to leverage new virtual and augmented reality COTS" hardware to enable ready, relevant learning on land and at-sea. However, three research and development issues need to be resolved"" in order to develop and deploy a more functional, more useful product that better realizes the training goals of Surface Warfare Of""ficers (SWO), Enlisted Quartermasters (QMs), and of the Sailor 2025 program. Furthermore, making RoR~s underlying ship navigation an"d movement simulation engine available to other projects within the Navigation and Ship handling Training and Assessment Tools (NSTA"T) program would catalyze other projects~ potential use for shipboard learning, mission rehearsal, and ready, relevant learning. Suc""h a virtual reality enhanced NSTAT would be adaptive, portable, and would potentially strengthen learning in the classroom during sc""hool hours, enable learning in a BOQ room after hours, or on the ship, and progressively build navigation and ship handling skills a""nytime, anywhere. We thus propose to investigate and resolve three issues on the critical path to developing and delivering an adapt""ive, VR-enabled, portable Rules of the Road (RoR) standalone, intelligent simulation trainer to the Surface Warfare Officer~s School"" (SWOS) in Newport, RI. First, we need to investigate new Virtual and Augmented Reality (VAR) hardware and software to determine opt""imal interaction design for optimal learning. Second, we need to investigate and develop optimal-fidelity ship simulations that enab""le portability without sacrificing training effectiveness. Third, we need to develop automated, student-adaptive, scenario generator""s that cover the wider range of variables relevant to NSTAT. These needs directly impact training realism, effectiveness, and portab"ility.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 05, 2017
- Source ID
- N000141712558
Entities
People
- Sushil J. Louis
Organizations
- Office of Naval Research
- United States Navy
- University of Nevada, Reno