Optimal Path Planning of a Target Following Fixed Wing UAV Using Sequential Decision Processes

Abstract

In this work, we consider the optimal path of a fixed-wing unmanned aerial vehicle (UAV) tracking a mobile surface target. One of the limitations of fixed-wing UAVs in tracking mobile targets is the lack of hovering capability when the target moves much slower than the minimum UAV speed, requiring the UAV maintain an orbit about the target. In this paper, we propose a method to find the optimal policy for fixed-wing UAVs to minimize the location uncertainty of a mobile target. using a grid-based Markov Decisive Process (MDP), we process a policy iteration algorithm offline to find the optimal UAV path in a discretized state space. Based on the offline optimal policy, we generate a finer grid MDP for the region of interest to efficiently process an online policy iteration to find in real-time the optimal trajectory for a UAV. We validate the proposed algorithm using computer simulations. Comparing the simulation results with other methods, we show that the proposed method has up to 13% decrease in error uncertainty than ones resulted using conventional methods.

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Document Details

Document Type
Technical Report
Publication Date
Jul 22, 2013
Accession Number
AD1022260

Entities

People

  • Daniel Pack
  • Hyukseong Kwon
  • Josiah A. Yoder
  • Stanley S. Baek

Organizations

  • United States Air Force Academy

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Computer Simulations
  • Iterations
  • Motion Planning
  • Simulations
  • Surface Targets
  • Targets
  • Uncertainty
  • Unmanned Aerial Vehicles
  • Vehicles

Fields of Study

  • Computer science
  • Engineering

Readers

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Technology Areas

  • Autonomy
  • Space
  • Space - Spacecraft Maneuvers