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Parallel and distributed computing for UAVs trajectory planning

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Abstract

The problem of generating optimal flight trajectories for an unmanned aerial vehicle in the presence of no-fly zones is computationally expensive. It is usually solved offline, at least for those parts which cannot satisfy real time constraints. An example is the core paths graph algorithm, which discretizes the operational flight scenario with a finite dimensional grid of positions-directions pairs. A weighted and oriented graph is then defined, wherein the nodes are the earlier mentioned grid points and the arcs represent minimum length trajectories compliant with obstacle avoidance constraints. This paper investigates the exploitation of two parallel programming techniques to reduce the lead time of the core paths graph algorithm. The former employs some parallelization techniques for multi-core and/or multi-processor platforms. The latter is targeted to a distributed fleet of unmanned aerial vehicles. Here the statement of the problem and preliminary development are discussed. A two-dimensional scenario is analysed by way of example to show the applicability and the effectiveness of the approaches.

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Authors and Affiliations

  1. Soft Computing Laboratory, CIRA (Italian Aerospace Research Centre), Capua, Italy

    Domenico Pascarella

  2. Department of Industrial and Information Engineering, Second University of Naples, Aversa, Italy

    Salvatore Venticinque, Rocco Aversa, Massimiliano Mattei & Luciano Blasi

Authors
  1. Domenico Pascarella
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  2. Salvatore Venticinque
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  3. Rocco Aversa
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  4. Massimiliano Mattei
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  5. Luciano Blasi
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Correspondence to Domenico Pascarella.

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Pascarella, D., Venticinque, S., Aversa, R. et al. Parallel and distributed computing for UAVs trajectory planning. J Ambient Intell Human Comput 6, 773–782 (2015). https://doi.org/10.1007/s12652-015-0282-y

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  • DOI: https://doi.org/10.1007/s12652-015-0282-y

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