IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i6p1413-d1097518.html
   My bibliography  Save this article

Trajectories Generation for Unmanned Aerial Vehicles Based on Obstacle Avoidance Located by a Visual Sensing System

Author

Listed:
  • Luis Felipe Muñoz Mendoza

    (Departamento de Electro–Fotónica, Centro Universitario de Ciencias Exactas e Ingenierías (C.U.C.E.I.), Universidad de Guadalajara (U. de G.), Blvd. M. García Barragán 1421, Guadalajara 44410, Jalisco, Mexico)

  • Guillermo García-Torales

    (Departamento de Electro–Fotónica, Centro Universitario de Ciencias Exactas e Ingenierías (C.U.C.E.I.), Universidad de Guadalajara (U. de G.), Blvd. M. García Barragán 1421, Guadalajara 44410, Jalisco, Mexico)

  • Cuauhtémoc Acosta Lúa

    (Departamento de Ciencias Tecnológicas, Centro Universitario de La Ciénega, Universidad de Guadalajara, Av. Universidad 1115, Ocotlán 47820, Jalisco, Mexico
    Center of Excellence DEWS, University of L’Aquila, Via Vetoio, Loc. Coppito, 67100 L’Aquila, Italy)

  • Stefano Di Gennaro

    (Center of Excellence DEWS, University of L’Aquila, Via Vetoio, Loc. Coppito, 67100 L’Aquila, Italy
    Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, Via Vetoio, Loc. Coppito, 67100 L’Aquila, Italy)

  • José Trinidad Guillen Bonilla

    (Departamento de Electro–Fotónica, Centro Universitario de Ciencias Exactas e Ingenierías (C.U.C.E.I.), Universidad de Guadalajara (U. de G.), Blvd. M. García Barragán 1421, Guadalajara 44410, Jalisco, Mexico)

Abstract

In this work, vectorial trajectories for unmanned aerial vehicles are completed based on a new algorithm named trajectory generation based on object avoidance (TGBOA), which is presented using a UAV camera as a visual sensor to define collision-free trajectories in scenarios with randomly distributed objects. The location information of the objects is collected by the visual sensor and processed in real-time. This proposal has two advantages. First, this system improves efficiency by focusing the algorithm on object detection and drone position, thus reducing computational complexity. Second, online trajectory references are generated and updated in real-time. To define a collision-free trajectory and avoid a collision between the UAV and the detected object, a reference is generated and shown by the vector, symmetrical, and parametric equations. Such vectors are used as a reference in a PI-like controller based on the Newton–Euler mathematical model. Experimentally, the TGBOA algorithm is corroborated by developing three experiments where the F-450 quadcopter, MATLAB ® 2022ª, PI-like controller, and Wi-Fi communication are applied. The TGBOA algorithm and the PI-like controller show functionality because the controller always follows the vector generated due to the obstacle avoidance.

Suggested Citation

  • Luis Felipe Muñoz Mendoza & Guillermo García-Torales & Cuauhtémoc Acosta Lúa & Stefano Di Gennaro & José Trinidad Guillen Bonilla, 2023. "Trajectories Generation for Unmanned Aerial Vehicles Based on Obstacle Avoidance Located by a Visual Sensing System," Mathematics, MDPI, vol. 11(6), pages 1-25, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1413-:d:1097518
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/6/1413/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/6/1413/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wenhui Wu & Xin Jin & Yang Tang, 2020. "Vision-based trajectory tracking control of quadrotors using super twisting sliding mode control," Cyber-Physical Systems, Taylor & Francis Journals, vol. 6(4), pages 207-230, October.
    2. José Trinidad Guillén-Bonilla & Claudia Carolina Vaca García & Stefano Di Gennaro & María Eugenia Sánchez Morales & Cuauhtémoc Acosta Lúa, 2020. "Vision-Based Nonlinear Control of Quadrotors Using the Photogrammetric Technique," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-10, November.
    Full references (including those not matched with items on IDEAS)

    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.

      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:gam:jmathe:v:11:y:2023:i:6:p:1413-:d:1097518. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.