Testing and evaluation of a wearable augmented reality system for natural outdoor environments

被引:3
|
作者
Roberts, David [1 ]
Menozzi, Alberico [1 ]
Cook, James [1 ]
Sherrill, Todd [1 ]
Snarski, Stephen [1 ]
Russler, Pat [1 ]
Clipp, Brian [1 ]
Karl, Robert [1 ]
Wenger, Eric [1 ]
Bennett, Matthew [1 ]
Mauger, Jennifer [1 ]
Church, William [1 ]
Towles, Herman [1 ]
MacCabe, Stephen [1 ]
Webb, Jeff [1 ]
Lupo, Jasper [1 ]
Frahm, Jan-Michael
Dunn, Enrique
Leslie, Christoper
Welch, Greg
机构
[1] Appl Res Associates, Raleigh, NC 27615 USA
关键词
pose estimation; augmented reality; geo-registered icons; head tracking; soldier-worn; see-through display;
D O I
10.1117/12.2015621
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This paper describes performance evaluation of a wearable augmented reality system for natural outdoor environments. Applied Research Associates (ARA), as prime integrator on the DARPA ULTRA-Vis (Urban Leader Tactical, Response, Awareness, and Visualization) program, is developing a soldier-worn system to provide intuitive 'heads-up' visualization of tactically-relevant geo-registered icons. Our system combines a novel pose estimation capability, a helmet-mounted see-through display, and a wearable processing unit to accurately overlay geo-registered iconography (e. g., navigation waypoints, sensor points of interest, blue forces, aircraft) on the soldier's view of reality. We achieve accurate pose estimation through fusion of inertial, magnetic, GPS, terrain data, and computer-vision inputs. We leverage a helmet-mounted camera and custom computer vision algorithms to provide terrain-based measurements of absolute orientation (i.e., orientation of the helmet with respect to the earth). These orientation measurements, which leverage mountainous terrain horizon geometry and mission planning landmarks, enable our system to operate robustly in the presence of external and body-worn magnetic disturbances. Current field testing activities across a variety of mountainous environments indicate that we can achieve high icon geo-registration accuracy (<10mrad) using these vision-based methods.
引用
收藏
页数:16
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