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Aerial Vehicle Search-Path Optimization: A Novel Method for Emergency Operations

Author

Listed:
  • Manon Raap

    (Universität der Bundeswehr München)

  • Silja Meyer-Nieberg

    (Universität der Bundeswehr München)

  • Stefan Pickl

    (Universität der Bundeswehr München)

  • Martin Zsifkovits

    (Universität der Bundeswehr München)

Abstract

This paper presents a novel search-path optimization method for moving target search by an aerial vehicle, applicable to realistically sized search areas. For such missions, long endurance vehicles are needed, which are usually fixed-winged. The proposed method accounts for flight kinematics of fixed-wing and rotary-wing aerial vehicles. It additionally accounts for movements of the target, considerably increasing complexity of search-path optimization, compared to a static target. The objective is to maximize the probability to detect a conditionally deterministic moving target within a given time period. We propose a first K-step-lookahead planning method that takes flight kinematic constraints into account and in which the target and platform state space are heterogeneous. It consists of a binary integer linear program that yields a physically feasible search-path, while maximizing the probability of detection. It is based on the Max-K-Coverage problem, as it selects K waypoints while maximizing the probability that a target is within the field of view of a platform at one of these waypoints. This K-step-lookahead planning method is embedded in an iterative framework, where the probability of overlooking a target is fed back to the controller after observations are made. Simulations show the applicability and effectiveness of this method.

Suggested Citation

  • Manon Raap & Silja Meyer-Nieberg & Stefan Pickl & Martin Zsifkovits, 2017. "Aerial Vehicle Search-Path Optimization: A Novel Method for Emergency Operations," Journal of Optimization Theory and Applications, Springer, vol. 172(3), pages 965-983, March.
    • Handle: RePEc:spr:joptap:v:172:y:2017:i:3:d:10.1007_s10957-016-1014-y
    DOI: 10.1007/s10957-016-1014-y
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    References listed on IDEAS

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    1. James N. Eagle & James R. Yee, 1990. "An Optimal Branch-and-Bound Procedure for the Constrained Path, Moving Target Search Problem," Operations Research, INFORMS, vol. 38(1), pages 110-114, February.
    2. Lau, Haye & Huang, Shoudong & Dissanayake, Gamini, 2008. "Discounted MEAN bound for the optimal searcher path problem with non-uniform travel times," European Journal of Operational Research, Elsevier, vol. 190(2), pages 383-397, October.
    3. Joseph Foraker & Johannes O. Royset & Isaac Kaminer, 2016. "Search-Trajectory Optimization: Part II, Algorithms and Computations," Journal of Optimization Theory and Applications, Springer, vol. 169(2), pages 550-567, May.
    4. Joseph Foraker & Johannes O. Royset & Isaac Kaminer, 2016. "Search-Trajectory Optimization: Part I, Formulation and Theory," Journal of Optimization Theory and Applications, Springer, vol. 169(2), pages 530-549, May.
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    2. Morin, Michael & Abi-Zeid, Irène & Quimper, Claude-Guy, 2023. "Ant colony optimization for path planning in search and rescue operations," European Journal of Operational Research, Elsevier, vol. 305(1), pages 53-63.

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