Anomaly detection and target prioritization in planetary imagery via the automated global feature analyzer (AGFA): Progress towards a driver for autonomous C4ISR missions

Wolfgang Fink, Alexander J.W. Brooks, Mark A. Tarbell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The Automated Global Feature AnalyzerTM (AGFATM) is a generically applicable automated sensor-data-fusion, feature extraction, feature vector clustering, anomaly detection, and target prioritization framework. AGFATM operates in the respective feature space delivered by the sensor(s). In this paper we provide an overview of the inner workings of AGFATMand apply AGFATM to planetary imagery, representative of past, current, and future planetary missions, to demonstrate its automated and objective (i.e., unbiased) anomaly detection and target prioritization (i.e., region-of-interest delineation) capabilities. Imaged operational areas are locally processed via a cascade of image segmentation, visual and geometric feature extraction, agglomerative clustering, and principal components analysis. Resulting clusters are labeled based on relative size and location in feature space. Anomalous regions may be considered immediate targets for follow-up in-situ investigation by local robotic agents, which can be directed via autonomous telecommanding, e.g., as part of a Tier-Scalable Reconnaissance mission architecture. These capabilities will be essential for driving fully autonomous C4ISR missions of the future, since the speed of light prohibits "real time" Earth-controlled conduct of planetary exploration beyond the Moon.

Original languageEnglish (US)
Title of host publicationMicro- and Nanotechnology Sensors, Systems, and Applications X
EditorsM. Saif Islam, Thomas George, Achyut K. Dutta
PublisherSPIE
ISBN (Electronic)9781510617896
DOIs
StatePublished - 2018
Event2018 Micro- and Nanotechnology (MNT) Sensors, Systems, and Applications X Conference - Orlando, United States
Duration: Apr 15 2018Apr 19 2018

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10639
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other2018 Micro- and Nanotechnology (MNT) Sensors, Systems, and Applications X Conference
CountryUnited States
CityOrlando
Period4/15/184/19/18

Keywords

  • Agglomerative clustering
  • Autonomous CISR systems
  • Autonomous decision making
  • Multi-Tiered robotic exploration architectures
  • Objective anomaly detection
  • Principal components analysis
  • Sensor-data-fusion framework
  • Target prioritization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Fink, W., Brooks, A. J. W., & Tarbell, M. A. (2018). Anomaly detection and target prioritization in planetary imagery via the automated global feature analyzer (AGFA): Progress towards a driver for autonomous C4ISR missions. In M. S. Islam, T. George, & A. K. Dutta (Eds.), Micro- and Nanotechnology Sensors, Systems, and Applications X [106391Z] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10639). SPIE. https://doi.org/10.1117/12.2303795