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The Game of Drones: rapid agent-based machine-learning models for multi-UAV path planning

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Abstract

The goal of this article is to provide basic modeling and simulation techniques for systems of multiple interacting Unmanned Aerial Vehicles, so called “swarms”, for applications in mapping. Also, the paper illustrates the application of basic machine-learning algorithms to optimize their information gathering. Numerical examples are provided to illustrate the concepts.

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Notes

  1. There are other modeling paradigms, for example mimicing ant colonies [16] which exhibit foraging-type behavior and trail-laying-trail-following mechanisms for finding food sources (see Kennedy and Eberhart [12] and Bonabeau et. al [16], Dorigo et. al,  [17], Bonabeau et. al [16], Bonabeau and Meyer [18] and Fiorelli et al [19]).

  2. The parameters in the model will be optimized shortly.

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  1. Department of Mechanical Engineering, University of California, 6195 Etcheverry Hall, Berkeley, CA, 94720-1740, USA

    T. I. Zohdi

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Zohdi, T.I. The Game of Drones: rapid agent-based machine-learning models for multi-UAV path planning. Comput Mech 65, 217–228 (2020). https://doi.org/10.1007/s00466-019-01761-9

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