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Diversified local search for the optimal layout of beacons in an indoor positioning system

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  • Manuel Laguna
  • Javier Roa
  • Antonio Jiménez
  • Fernando Seco

Abstract

The navigation of Autonomous Guided Vehicles (AGVs) in industrial environments is often controlled by positioning systems based on landmarks or artificial beacons. In these systems, the position of an AGV navigating in an interior space is determined by the calculation of its relative distance to beacons, whose location is known in advance. A fundamental design problem associated with landmark navigation systems consists in determining the optimal location of the minimum number of beacons necessary to achieve a desired level of accuracy and reliability. A local search procedure coupled with a diversification strategy is developed for this problem. Comparisons with an earlier solution method based on genetic algorithms are provided and it is shown that the proposed procedure finds better designs in a fraction of the computational time employed by the genetic algorithm.

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  • Manuel Laguna & Javier Roa & Antonio Jiménez & Fernando Seco, 2009. "Diversified local search for the optimal layout of beacons in an indoor positioning system," IISE Transactions, Taylor & Francis Journals, vol. 41(3), pages 247-259.
    • Handle: RePEc:taf:uiiexx:v:41:y:2009:i:3:p:247-259
    DOI: 10.1080/07408170802369383
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    1. Tsai, Chieh-Yuan & Chang, Hui-Ting & Kuo, Ren Jieh, 2017. "An ant colony based optimization for RFID reader deployment in theme parks under service level consideration," Tourism Management, Elsevier, vol. 58(C), pages 1-14.

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