• DocumentCode
    3486811
  • Title

    Route planning algorithms for unmanned aerial vehicles with refueling constraints

  • Author

    Sundar, K. ; Rathinam, Sivakumar

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • fYear
    2012
  • fDate
    27-29 June 2012
  • Firstpage
    3266
  • Lastpage
    3271
  • Abstract
    Small UAVs are currently used in several monitoring applications to monitor a set of targets and collect relevant data. One of the main constraints that characterize a small UAV is the maximum amount of fuel the vehicle carry. In this article, we consider a single UAV routing problem where there are multiple depots and the vehicle is allowed to refuel at any depot. The objective of the problem is to find a path for the UAV such that each target is visited at least once by the vehicle, the fuel constraint is never violated along the path for the UAV, and the total cost of the edges present in the path is a minimum. We first develop a mixed integer, linear programming formulation to solve the problem optimally. We also propose fast and efficient construction and improvement heuristics to solve the same. Computational results are also presented to corroborate the solution quality and the running times of all the algorithms.
  • Keywords
    autonomous aerial vehicles; fuel; integer programming; linear programming; UAV routing problem; fuel constraint; mixed integer-linear programming formulation; monitoring applications; multiple depots; refueling constraints; route planning algorithms; small UAV; target monitoring; unmanned aerial vehicles; Approximation algorithms; Approximation methods; Equations; Fuels; Heuristic algorithms; Routing; Vehicles; Fuel Constraints; Local Search Heuristics; Orienteering Problem; Traveling Salesman Problem; k-opt;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2012
  • Conference_Location
    Montreal, QC
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4577-1095-7
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2012.6315620
  • Filename
    6315620