The problem of generating optimal flight trajectories in the presence of no-fly zones and/or obstacles is computationally expensive. It is usually solved offline, at least for those parts which cannot satisfy real time constraints. Here we investigate the exploitation of two parallel programming techniques to reduce the lead time. The former employs some parallelization techniques formulti-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.

Aparallel and adistributed implementation of thecore paths graphalgorithm / Pascarella, D.; Venticinque, S.; Aversa, R.; Mattei, M.; Blasi, L.. - 570:(2015), pp. 417-426. [10.1007/978-3-319-10422-5_43]

Aparallel and adistributed implementation of thecore paths graphalgorithm

Mattei M.;
2015

Abstract

The problem of generating optimal flight trajectories in the presence of no-fly zones and/or obstacles is computationally expensive. It is usually solved offline, at least for those parts which cannot satisfy real time constraints. Here we investigate the exploitation of two parallel programming techniques to reduce the lead time. The former employs some parallelization techniques formulti-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.
2015
Aparallel and adistributed implementation of thecore paths graphalgorithm / Pascarella, D.; Venticinque, S.; Aversa, R.; Mattei, M.; Blasi, L.. - 570:(2015), pp. 417-426. [10.1007/978-3-319-10422-5_43]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/876739
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