Fuzzy Logic Based UAV Allocation and Coordination

Abstract

A fuzzy logic resource allocation algorithm that enables a collection of unmanned aerial vehicles (UAVs) to automatically cooperate will be discussed. The goal of the UAVs' coordinated effort is to measure the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy logic-based planning algorithm determines the optimal trajectory and points each UAV will sample, while taking into account the UAVs' risk, risk tolerance, reliability, and mission priority for sampling in certain regions. It also considers fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV renders the UAVs autonomous, allowing them to change course immediately without consulting with any commander, request other UAVs to help, and change the points that will be sampled when observing interesting phenomena. Simulations show the ability of the control algorithm to allow UAVs to effectively cooperate to increase the UAV team's likelihood of success.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2006
Accession Number
ADA524150

Entities

People

  • James F. Smith Iii
  • Thanhvu H. Nguyen

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Autonomous Systems
  • Control Systems
  • Flight Paths
  • Fuzzy Logic
  • Logic
  • Refraction
  • Refractive Index
  • Reliability
  • Sampling
  • Self Organizing Systems
  • Sensor Fusion
  • Simulations
  • Unmanned Aerial Vehicles
  • Vehicles

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Artificial Intelligence
  • Distributed Systems and Data Platform Development

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control
  • Autonomy - Human-Robot Interaction
  • Autonomy - UAVs