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Dynamic Data-Driven UAV Network for Plume Characterization

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Technical Report,15 Feb 2013,14 Feb 2016

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University of Florida Gainesville, United States

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Targeted, intelligent sensor networks have important applications in a tremendous range of situations, including toxic plume characterization, Intelligence, Surveillance and Reconnaissance ISR, environmental monitoring, weather forecasting, and disaster management and response. Data driven operation of a mobile sensor network enables asset allocation to regions with highest impact on the mission success. We studied a dynamic data driven DDD approach to operation of a heterogeneous team of unmanned aerial vehicles UAVs or microminiature aerial vehicles MAVs for toxic plume characterization or similar ISR missions in complex domains. The proposed approach consists of two DDD loops. These are the DDD simulation loop and DDD sensor placement loop. The integrated feedback loops connect simulations and data analysis techniques with mobile sensor data collection where simulations and measurements become a symbiotic feedback control system where simulations inform measurement locations and the measured data augments simulations. We have developed several model reduction strategies to reduce the computational complexity of the simulation loop.

Subject Categories:

  • Pilotless Aircraft
  • Navigation and Guidance
  • Operations Research
  • Cybernetics

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