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Modelling multi-rotor UAVs swarm deployment using virtual pheromones

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  • Fidel Aznar
  • Mar Pujol
  • Ramón Rizo
  • Carlos Rizo

Abstract

In this work, a swarm behaviour for multi-rotor Unmanned Aerial Vehicles (UAVs) deployment will be presented. The main contribution of this behaviour is the use of a virtual device for quantitative sematectonic stigmergy providing more adaptable behaviours in complex environments. It is a fault tolerant highly robust behaviour that does not require prior information of the area to be covered, or to assume the existence of any kind of information signals (GPS, mobile communication networks …), taking into account the specific features of UAVs. This behaviour will be oriented towards emergency tasks. Their main goal will be to cover an area of the environment for later creating an ad-hoc communication network, that can be used to establish communications inside this zone. Although there are several papers on robotic deployment it is more difficult to find applications with UAV systems, mainly because of the existence of various problems that must be overcome including limitations in available sensory and on-board processing capabilities and low flight endurance. In addition, those behaviours designed for UAVs often have significant limitations on their ability to be used in real tasks, because they assume specific features, not easily applicable in a general way. Firstly, in this article the characteristics of the simulation environment will be presented. Secondly, a microscopic model for deployment and creation of ad-hoc networks, that implicitly includes stigmergy features, will be shown. Then, the overall swarm behaviour will be modeled, providing a macroscopic model of this behaviour. This model can accurately predict the number of agents needed to cover an area as well as the time required for the deployment process. An experimental analysis through simulation will be carried out in order to verify our models. In this analysis the influence of both the complexity of the environment and the stigmergy system will be discussed, given the data obtained in the simulation. In addition, the macroscopic and microscopic models will be compared verifying the number of predicted individuals for each state regarding the simulation.

Suggested Citation

  • Fidel Aznar & Mar Pujol & Ramón Rizo & Carlos Rizo, 2018. "Modelling multi-rotor UAVs swarm deployment using virtual pheromones," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-20, January.
    • Handle: RePEc:plo:pone00:0190692
    DOI: 10.1371/journal.pone.0190692
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    References listed on IDEAS

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    1. Tingxi Wen & Zhongnan Zhang & Kelvin K L Wong, 2016. "Multi-Objective Algorithm for Blood Supply via Unmanned Aerial Vehicles to the Wounded in an Emergency Situation," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-22, May.
    2. Matthias Vigelius & Bernd Meyer & Geoffrey Pascoe, 2014. "Multiscale Modelling and Analysis of Collective Decision Making in Swarm Robotics," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-19, November.
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