Tier-scalable reconnaissance: the future in autonomous C4ISR systems has arrived: progress towards an outdoor testbed
AffiliationUniv Arizona, Coll Engn, Visual & Autonomous Explorat Syst Res Lab
KeywordsAutonomous (CISR)-I-4 systems
smart service systems
navigational behavior motifs
objective anomaly detection
MetadataShow full item record
PublisherSPIE-INT SOC OPTICAL ENGINEERING
CitationWolfgang Fink, Alexander J.-W. Brooks, Mark A. Tarbell, James M. Dohm, "Tier-scalable reconnaissance: the future in autonomous C4ISR systems has arrived: progress towards an outdoor testbed", Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 1019422 (18 May 2017); doi: 10.1117/12.2257333; http://dx.doi.org/10.1117/12.2257333
Rights© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
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AbstractAutonomous reconnaissance missions are called for in extreme environments, as well as in potentially hazardous (e.g., the theatre, disaster-stricken areas, etc.) or inaccessible operational areas (e.g., planetary surfaces, space). Such future missions will require increasing degrees of operational autonomy, especially when following up on transient events. Operational autonomy encompasses: (1) Automatic characterization of operational areas from different vantages (i.e., spaceborne, airborne, surface, subsurface); (2) automatic sensor deployment and data gathering; (3) automatic feature extraction including anomaly detection and region-of-interest identification; (4) automatic target prediction and prioritization; (5) and subsequent automatic (re-) deployment and navigation of robotic agents. This paper reports on progress towards several aspects of autonomous (CISR)-I-4 systems, including: Caltech-patented and NASA award-winning multi-tiered mission paradigm, robotic platform development (air, ground, water-based), robotic behavior motifs as the building blocks for autonomous telecommanding, and autonomous decision making based on a Caltech-patented framework comprising sensor-data-fusion (feature-vectors), anomaly detection (clustering and principal component analysis), and target prioritization (hypothetical probing).
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