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Trajectory Planning for Aerial Vehicles in the Area Coverage Problem with Nearby Obstacles

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Modelling and Simulation for Autonomous Systems (MESAS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11472))

Abstract

In this paper, we address the coverage path planning with curvature-constrained paths for a fixed-wing aerial vehicle. The studied problem is to provide a cost-efficient solution to cover a given area by the vehicle sensor from the specified altitude to provide a sufficient level of details in the captured snapshots of the area. In particular, we focus on scenarios where the area to be covered is surrounded by nearby obstacles such as trees or buildings, and the vehicle has to avoid collisions with the obstacles but maximizes the area coverage. We propose an extension of the existing coverage planning algorithm to determine a shortest collision-free path that is accompanied by Dubins Airplane model to satisfy the motion constraints of the vehicle. The reported results support the feasibility of the proposed approach to avoid nearby obstacles by optimal adjustments of the vehicle altitude while the requested complete coverage is satisfied. If such a solution is not found because of too close obstacles, a feasible solution maximizing the coverage is provided.

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Acknowledgement

This work has been supported by the Czech Science Foundation (GAČR) under research Project No. 16-24206S and Project No. 19-20238S.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 166 27, Prague, Czech Republic

    Jakub Marek, Petr Váňa & Jan Faigl

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  1. Jakub Marek
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  2. Petr Váňa
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  3. Jan Faigl
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Corresponding author

Correspondence to Petr Váňa .

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Editors and Affiliations

  1. NATO Modelling and Simulation Centre of Excellence, Rome, Italy

    Jan Mazal

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Marek, J., Váňa, P., Faigl, J. (2019). Trajectory Planning for Aerial Vehicles in the Area Coverage Problem with Nearby Obstacles. In: Mazal, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2018. Lecture Notes in Computer Science(), vol 11472. Springer, Cham. https://doi.org/10.1007/978-3-030-14984-0_18

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  • DOI: https://doi.org/10.1007/978-3-030-14984-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14983-3

  • Online ISBN: 978-3-030-14984-0

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