A Multi-agent UAV Swarm for Automatic Target Recognition

  • Prithviraj Dasgupta
  • Stephen O’Hara
  • Plamen Petrov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3890)


We address the problem of automatic target recognition (ATR) using a multi-agent swarm of unmanned aerial vehicles(UAVs) deployed within a reconnaissance area. Traditionally, ATR is performed by UAVs that fly within the reconnaissance area to collect image data through sensors and upload the data to a central base station for analyzing and identifying potential targets. The centralized approach to ATR introduces several problems including scalability with the number of UAVs, network delays in communicating with the central location, and, susceptibility of the system to malicious attacks on the central location. In this paper, we describe a multi-agent system of UAVs to perform ATR. We assume that each UAV has limited computational capabilities and target identification can be performed by several UAVs that combine their resources including their computational capabilities. The UAVs employ a swarming algorithm implemented through software agents to congregate at and identify potential targets, and, a gossiping mechanism to disseminate information within the swarm.


Global Position System Potential Target Multiagent System Unmanned Aerial Vehicle Pheromone Trail 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Prithviraj Dasgupta
    • 1
  • Stephen O’Hara
    • 1
  • Plamen Petrov
    • 2
  1. 1.Department of Computer ScienceUniversity of NebraskaOmahaUSA
  2. 2.21st Century Systems Inc.OmahaUSA

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