Daniel Mandl, Rob Sohlberg, Chris Justice, Stephen Ungar, Troy Ames, Stuart Frye, Steve Chien, Daniel Tran, Patrice Cappelaere, Linda Derezinski, Granville Paules, Don Sullivan, Liping Di, Stephan Kolitz
KEYWORDS: Sensors, Satellites, Surface plasmons, Web services, Internet, Web 2.0 technologies, Standards development, Data processing, Received signal strength, MODIS
This paper describes the work being managed by the NASA Goddard Space Flight Center (GSFC) Information System
Division (ISD) under a NASA Earth Science Technology Office (ESTO) Advanced Information System Technology
(AIST) grant to develop a modular sensor web architecture which enables discovery of sensors and workflows that can
create customized science via a high-level service-oriented architecture based on Open Geospatial Consortium (OGC)
Sensor Web Enablement (SWE) web service standards. These capabilities serve as a prototype to a user-centric
architecture for Global Earth Observing System of Systems (GEOSS). This work builds and extends previous sensor
web efforts conducted at NASA/GSFC using the Earth Observing 1 (EO-1) satellite and other low-earth orbiting
satellites.
The National Aeronautics and Space Administration (NASA), Aeronautics Research Mission Directorate, is developing Intelligent Mission Management (IMM) technology for Uninhabited Aerial Vehicles (UAV’s) under the Vehicle Systems Program’s Autonomous Robust Avionics Project. The objective of the project is to develop air vehicle and associated ground element technology to enhance mission success by increasing mission return and reducing mission risk. Unanticipated science targets, uncertain conditions and changing mission requirements can all influence a flight plan and may require human intervention during the flight; however, time delays and communications bandwidth limit opportunities for operator intervention. To meet these challenges, we will develop UAV-specific technologies enabling goal-directed autonomy, i.e. the ability to redirect the flight in response to current conditions and the current goals of the flight. Our approach divides goal-directed autonomy into two components, an on-board Intelligent Agent Architecture (IAA) and a ground based Collaborative Decision Environment (CDE). These technologies cut across all aspects of a UAV system, including the payload, inner- and outer-loop onboard control, and the operator’s ground station.
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