IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i12p2181-d1285311.html
   My bibliography  Save this article

Enabling Autonomous Navigation on the Farm: A Mission Planner for Agricultural Tasks

Author

Listed:
  • Ruth Cordova-Cardenas

    (Centre for Automation and Robotics (UPM-CSIC), 28500 Arganda del Rey, Madrid, Spain)

  • Luis Emmi

    (Centre for Automation and Robotics (UPM-CSIC), 28500 Arganda del Rey, Madrid, Spain)

  • Pablo Gonzalez-de-Santos

    (Centre for Automation and Robotics (UPM-CSIC), 28500 Arganda del Rey, Madrid, Spain)

Abstract

This study presents the development of a route planner, called Mission Planner, for an agricultural weeding robot that generates efficient and safe routes both in the field and on the farm using a graph-based approach. This planner optimizes the robot’s motion throughout the farm and performs weed management tasks tailored for high-power laser devices in narrow-row crops (wheat, barley, etc.) and wide-row crops (sugar beet, maize, etc.). Three main algorithms were integrated: Dijkstra’s algorithm to find the most optimal route on the farm, the VRMP (Visibility Road-Map Planner) method to select the route within cultivated fields when roads are not visible, and an improved version of the Hamiltonian path to find the best route between the crop lines. The results support the effectiveness of the strategies implemented, demonstrating that a robot can safely and efficiently navigate through the entire farm and perform an agricultural treatment, in this case study, in laser-based weed management. In addition, it was found that the route planner reduced the robot’s operation time, thus improving the overall efficiency of precision agriculture.

Suggested Citation

  • Ruth Cordova-Cardenas & Luis Emmi & Pablo Gonzalez-de-Santos, 2023. "Enabling Autonomous Navigation on the Farm: A Mission Planner for Agricultural Tasks," Agriculture, MDPI, vol. 13(12), pages 1-19, November.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:12:p:2181-:d:1285311
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/12/2181/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/12/2181/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. López-Riquelme, J.A. & Pavón-Pulido, N. & Navarro-Hellín, H. & Soto-Valles, F. & Torres-Sánchez, R., 2017. "A software architecture based on FIWARE cloud for Precision Agriculture," Agricultural Water Management, Elsevier, vol. 183(C), pages 123-135.
    2. Luis Emmi & Roemi Fernández & Pablo Gonzalez-de-Santos & Matteo Francia & Matteo Golfarelli & Giuliano Vitali & Hendrik Sandmann & Michael Hustedt & Merve Wollweber, 2023. "Exploiting the Internet Resources for Autonomous Robots in Agriculture," Agriculture, MDPI, vol. 13(5), pages 1-22, May.
    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.
    1. Jin Yuan & Wei Ji & Qingchun Feng, 2023. "Robots and Autonomous Machines for Sustainable Agriculture Production," Agriculture, MDPI, vol. 13(7), pages 1-4, July.
    2. Jiazheng Shen & Tang Sai Hong & Luxin Fan & Ruixin Zhao & Mohd Khairol Anuar b. Mohd Ariffin & Azizan bin As’arry, 2024. "Development of an Improved GWO Algorithm for Solving Optimal Paths in Complex Vertical Farms with Multi-Robot Multi-Tasking," Agriculture, MDPI, vol. 14(8), pages 1-26, August.
    3. Mabhaudhi, Tafadzwanashe & Dirwai, Tinashe Lindel & Taguta, Cuthbert & Sikka, Alok & Lautze, Jonathan, 2023. "Mapping Decision Support Tools (DSTs) on agricultural water productivity: A global systematic scoping review," Agricultural Water Management, Elsevier, vol. 290(C).
    4. Beata Michaliszyn-Gabryś & Joachim Bronder & Wanda Jarosz & Janusz Krupanek, 2024. "Potential of Eco-Weeding with High-Power Laser Adoption from the Farmers’ Perspective," Sustainability, MDPI, vol. 16(6), pages 1-26, March.
    5. Emin Guresci & Bedir Tekinerdogan & Önder Babur & Qingzhi Liu, 2024. "Feasibility of Low-Code Development Platforms in Precision Agriculture: Opportunities, Challenges, and Future Directions," Land, MDPI, vol. 13(11), pages 1-31, October.
    6. Luis Emmi & Roemi Fernández & Pablo Gonzalez-de-Santos & Matteo Francia & Matteo Golfarelli & Giuliano Vitali & Hendrik Sandmann & Michael Hustedt & Merve Wollweber, 2023. "Exploiting the Internet Resources for Autonomous Robots in Agriculture," Agriculture, MDPI, vol. 13(5), pages 1-22, May.
    7. Gaetano Rocco & Claudia Pipino & Claudio Pagano, 2023. "An Overview of Urban Mobility: Revolutionizing with Innovative Smart Parking Systems," Sustainability, MDPI, vol. 15(17), pages 1-17, September.
    8. Zinkernagel, Jana & Maestre-Valero, Jose. F. & Seresti, Sogol Y. & Intrigliolo, Diego S., 2020. "New technologies and practical approaches to improve irrigation management of open field vegetable crops," Agricultural Water Management, Elsevier, vol. 242(C).
    9. Krunal K. Punjani & Kala Mahadevan & Angappa Gunasekaran & V. V. Ravi Kumar & Sujata Joshi, 2023. "Cloud computing in agriculture: a bibliometric and network visualization analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3849-3883, August.
    10. Siva Rama Krishnan & M. K. Nallakaruppan & Rajeswari Chengoden & Srinivas Koppu & M. Iyapparaja & Jayakumar Sadhasivam & Sankaran Sethuraman, 2022. "Smart Water Resource Management Using Artificial Intelligence—A Review," Sustainability, MDPI, vol. 14(20), pages 1-28, October.
    11. Elena G. Popkova & Shakhlo T. Ergasheva & Nadezhda K. Savelyeva & Marija A. Troyanskaya, 2024. "Change Management for the Sustainable Development of the Agrarian Economy of Artificial Intelligence," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(1), pages 79-90, September.

    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:jagris:v:13:y:2023:i:12:p:2181-:d:1285311. 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.