Multivehicle Cooperative Military Training Simulation System Based on Augmented Reality The military training systems based on augmented reality(AR) present challenges for cooperation training and confrontation training. In this paper, we propose a multivehicle cooperative military training simulation system based on video seethrough AR. Our system combines robust tracking algorithm, realistic AR display and network module to overlay virtual forces accurately on each soldieru0027s realworld view. We present our tracking algorithm using a monocular camera in combination with an inertial measurement unit(IMU) and GPS in a loosely coupled Extended Kalman Filter(EKF)based framework to obtain robust and realtime pose estimation. Our AR display provides realtime dynamic painting of virtual forces, battlefield situational awareness, and visual feedback for a variety of training activities. The inserted virtual forces can move in a predefined trajectory and shoot real vehicles in the specified range. The network module is used to support multivehicle realtime cooperative training. We evaluate the accuracy of the tracking algorithm by comparing with DGPS. The consistency of rendering on different soldiersu0027 AR displays is analyzed. In addition, we test our distinctive multivehicle cooperative confrontation training system online in a small team.

Effects of RealWorld Visual Fidelity on AR Interface Assessment: A Case Study Using AR Headup Display Graphics in Driving Recent AR research efforts have explored the use of virtual environments to test augmented reality (AR) user interfaces. However, it is yet to be seen what effects the visual fidelity of such virtual environments may have on AR interface assessment, and specifically to what degree assessment results observed in a virtual world would apply to the real world. Automotive AR headup (HUD) interfaces provide a meaningful application area to examine this problem, especially given that immersive, 3Dgraphicsbased driving simulators are established tools to examine invehicle interfaces safely before testing in real vehicles. In this work, we present an argument that adequately assessing AR interfaces requires a suite of different measures, and that such measures should be considered when debating the appropriateness of virtual environments for AR interface assessment. We present a case study that examines how an AR interface presented via HUD effects driver performance and behavior in different virtual and real environments. Twelve participants completed the study measuring driver task performance, eye gaze behavior and situational awareness during AR guided navigation in lowand highfidelity virtual simulation, and an onroad environment. Our results suggest that the visual fidelity of the environmental in which an AR interface is assessed, could impact some measures of effectiveness. Discussion is guided by a proposed initial assessment classification for AR user interfaces that may serve to guide future discussions on AR interface evaluation, as well as the suitability of virtual environments for AR assessment.