Sensor fusion for swarms of unmanned aerial vehicles using modeling field theory

2005 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS'05: Modeling, Exploration, and Engineering

Volumn 2005, Issue , 2005, Pages 122-127

  Deming, Ross ^a   Perlovsky, Leonid ^b   Brockett, Roger ^c  

^a Air Force Research Laboratory   (United States)

^b AIR FORCE RESEARCH LABORATORY   (United States)

^c HARVARD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY DYNAMIC LOGIC; MODELING FIELD THEORY; SIGNAL-TO-CLUTTER TARGETS; VISUAL SENSORS;

AUTOMATION; COLLISION AVOIDANCE; CORRELATION METHODS; FUZZY SETS; IMAGE ANALYSIS; SENSOR DATA FUSION;

UNMANNED VEHICLES;

EID: 33745239249     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/KIMAS.2005.1427065     Document Type: Conference Paper

References (7)

1. Duda, R.O., Hart, P.E. (1973). Pattern Classification and Scene Analysis. Chap. 10, Wiley, New York, NY.
2. Jain, A.K. (1986). Fundamentals of Digital Image Processing. Chap.9, Prentice-Hall, Englewood Cliffs, NJ.
3. Office of the Secretary of Defense (2002). Unmanned Aerial Vehicles Roadmap 2002-2027
4. Perlovsky, L.I. (2001). Neural Networks and Intellect: using model-based concepts. Oxford University Press, New York, NY.
5. Wall,R. (2004). The Latest Leap. Aviation Week and Space Technology, September 6, pp.46-7.
6. Wall,R. (2004). On the Offensive. Aviation Week and Space Technology, September 6, pp.49-50.
7. Winkler, S., Vorsmann, P. (2004). Bird's-Eye View: GPS and Micro Aerial Vehicles. GPS World, October, pp. 14-22.