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A Vision-Based Motion Control Framework for Water Quality Monitoring Using an Unmanned Aerial Vehicle

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  • Fotis Panetsos

    (Control Systems Laboratory, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • Panagiotis Rousseas

    (Control Systems Laboratory, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

  • George Karras

    (Control Systems Laboratory, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece
    Department of Informatics and Telecommunications, University of Thessaly, 35100 Lamia, Greece)

  • Charalampos Bechlioulis

    (Control Systems Laboratory, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece
    Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece)

  • Kostas J. Kyriakopoulos

    (Control Systems Laboratory, School of Mechanical Engineering, National Technical University of Athens, 15780 Athens, Greece)

Abstract

In this paper, we present a vision-aided motion planning and control framework for the efficient monitoring and surveillance of water surfaces using an Unmanned Aerial Vehicle (UAV). The ultimate goal of the proposed strategy is to equip the UAV with the necessary autonomy and decision-making capabilities to support First Responders during emergency water contamination incidents. Toward this direction, we propose an end-to-end solution, based on which the First Responder indicates visiting and landing waypoints, while the envisioned strategy is responsible for the safe and autonomous navigation of the UAV, the refinement of the way-point locations that maximize the visible water surface area from the onboard camera, as well as the on-site refinement of the appropriate landing region in harsh environments. More specifically, we develop an efficient waypoint-tracking motion-planning scheme with guaranteed collision avoidance, a local autonomous exploration algorithm for refining the way-point location with respect to the areas visible to the drone’s camera, water, a vision-based algorithm for the on-site area selection for feasible landing and finally, a model predictive motion controller for the landing procedure. The efficacy of the proposed framework is demonstrated via a set of simulated and experimental scenarios using an octorotor UAV.

Suggested Citation

  • Fotis Panetsos & Panagiotis Rousseas & George Karras & Charalampos Bechlioulis & Kostas J. Kyriakopoulos, 2022. "A Vision-Based Motion Control Framework for Water Quality Monitoring Using an Unmanned Aerial Vehicle," Sustainability, MDPI, vol. 14(11), pages 1-23, May.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6502-:d:824603
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    References listed on IDEAS

    as
    1. Haiwen Yuan & Changshi Xiao & Supu Xiu & Wenqiang Zhan & Zhenyi Ye & Fan Zhang & Chunhui Zhou & Yuanqiao Wen & Qiliang Li, 2018. "A hierarchical vision-based localization of rotor unmanned aerial vehicles for autonomous landing," International Journal of Distributed Sensor Networks, , vol. 14(9), pages 15501477188, September.
    2. Ayamga, Matthew & Akaba, Selorm & Nyaaba, Albert Apotele, 2021. "Multifaceted applicability of drones: A review," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    Full references (including those not matched with items on IDEAS)

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    Keywords

    UAV; autonomy;

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