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UAV Path Planning for Area Coverage and Energy Consumption in Oil and Gas Exploration Environment

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Computational Logistics (ICCL 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14239))

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Abstract

This paper proposes a model for unmanned aerial vehicles (UAV) grid-based coverage path planning, considering coverage completeness and energy consumption in complex environments with multiple obstacles. The work is inspired by the need for more efficient approaches to oil and gas exploration, but other application areas where UAVs can be used to explore unknown environments can also benefit from this work. An energy consumption model is proposed that considers acceleration, deceleration, and turning manoeuvres, as well as the distance to obstacles, to more accurately simulate the UAV’s movement in different environments. Three different environments are modelled: desert, forest, and jungle. The energy-aware coverage path planning algorithm implemented seeks to reduce the energy consumption of a single drone while increasing coverage completeness. The model implementation and experiments were performed in the ROS/Gazebo simulation software. Obtained results show that the algorithm performs very well, with the drone able to manoeuvre itself in a combination of hills, valleys, rugged terrain, and steep topography while balancing coverage and energy consumption.

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Authors and Affiliations

  1. School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK

    Salim Sulaiman Maaji & Dario Landa-Silva

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  1. Salim Sulaiman Maaji
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  2. Dario Landa-Silva
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Correspondence to Salim Sulaiman Maaji .

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Editors and Affiliations

  1. Hochschule für Wirtschaft und Recht Berlin, Berlin, Germany

    Joachim R. Daduna

  2. Deutsches Zentrum für Luft- und Raumfahrt (DLR), Berlin, Germany

    Gernot Liedtke

  3. Deutsches Zentrum für Luft- und Raumfahrt (DLR), Berlin, Germany

    Xiaoning Shi

  4. University of Hamburg, Hamburg, Germany

    Stefan Voß

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Maaji, S.S., Landa-Silva, D. (2023). UAV Path Planning for Area Coverage and Energy Consumption in Oil and Gas Exploration Environment. In: Daduna, J.R., Liedtke, G., Shi, X., Voß, S. (eds) Computational Logistics. ICCL 2023. Lecture Notes in Computer Science, vol 14239. Springer, Cham. https://doi.org/10.1007/978-3-031-43612-3_29

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  • DOI: https://doi.org/10.1007/978-3-031-43612-3_29

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