IDEAS home Printed from https://ideas.repec.org/a/hin/complx/6879419.html
   My bibliography  Save this article

Intelligent UAV Map Generation and Discrete Path Planning for Search and Rescue Operations

Author

Listed:
  • Víctor San Juan
  • Matilde Santos
  • José Manuel Andújar

Abstract

Search and Rescue Operations (SAR) take place in any emergency situation where people are involved and their lives are at risk. These operations are nowadays carried out with the help of advanced technology, such as Unmanned Aerial Vehicles (UAVs). In this work, several methods are proposed to calculate the UAV discrete path planning. Previously, an intelligent characterization of the searching area is performed to estimate a potential risk/occupancy degree of the gridding map. This estimation is mainly based on fuzzy logic, considering different factors. Then, four methods are applied to calculate the path planning: an original proposal called attraction, fuzzy logic, ANFIS, and a PSO algorithm. All of them calculate the location of the waypoints to be followed by the UAVs to minimize the distance and the risk the people is exposed to. Then, these strategies are adapted to the possibility of having more than one UAV searching at the same time, and the swarm formation is discussed. Finally, these four solutions for path planning, including different number of UAVs, are tested in a real simulation scenario, and then the performance of each method is analyzed and compared with the others.

Suggested Citation

  • Víctor San Juan & Matilde Santos & José Manuel Andújar, 2018. "Intelligent UAV Map Generation and Discrete Path Planning for Search and Rescue Operations," Complexity, Hindawi, vol. 2018, pages 1-17, April.
    • Handle: RePEc:hin:complx:6879419
    DOI: 10.1155/2018/6879419
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2018/6879419.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2018/6879419.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2018/6879419?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Zhenglong Wu & Zhenyu Guan & Chengwei Yang & Jie Li, 2017. "Terminal Guidance Law for UAV Based on Receding Horizon Control Strategy," Complexity, Hindawi, vol. 2017, pages 1-19, May.
    2. E. G. Hernandez-Martinez & E. D. Ferreira-Vazquez & G. Fernandez-Anaya & J. J. Flores-Godoy, 2017. "Formation Tracking of Heterogeneous Mobile Agents Using Distance and Area Constraints," Complexity, Hindawi, vol. 2017, pages 1-13, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cesar Guevara & Matilde Santos, 2022. "Smart Patrolling Based on Spatial-Temporal Information Using Machine Learning," Mathematics, MDPI, vol. 10(22), pages 1-27, November.
    2. Lufeng Luo & Hanjin Wen & Qinghua Lu & Haojie Huang & Weilin Chen & Xiangjun Zou & Chenglin Wang, 2018. "Collision-Free Path-Planning for Six-DOF Serial Harvesting Robot Based on Energy Optimal and Artificial Potential Field," Complexity, Hindawi, vol. 2018, pages 1-12, November.
    3. Moisés Lodeiro-Santiago & Pino Caballero-Gil & Ricardo Aguasca-Colomo & Cándido Caballero-Gil, 2019. "Secure UAV-Based System to Detect Small Boats Using Neural Networks," Complexity, Hindawi, vol. 2019, pages 1-11, January.
    4. M. R. Mahendrini Fernando Ariyachandra & Gayan Wedawatta, 2023. "Digital Twin Smart Cities for Disaster Risk Management: A Review of Evolving Concepts," Sustainability, MDPI, vol. 15(15), pages 1-25, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mao Su & Lei Liu & Yongji Wang, 2018. "Integrated Estimation/Guidance Law against Exoatmospheric Maneuvering Targets," Complexity, Hindawi, vol. 2018, pages 1-19, December.
    2. Zhengquan Yang & Qing Zhang & Zengqiang Chen, 2019. "Formation Control of Multi-Agent Systems with Region Constraint," Complexity, Hindawi, vol. 2019, pages 1-6, December.
    3. Jesús Enrique Sierra & Matilde Santos, 2019. "Wind and Payload Disturbance Rejection Control Based on Adaptive Neural Estimators: Application on Quadrotors," Complexity, Hindawi, vol. 2019, pages 1-20, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:6879419. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.