IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v15y2025i8p882-d1637324.html
   My bibliography  Save this article

Mapping for Autonomous Navigation of Agricultural Robots Through Crop Rows Using UAV

Author

Listed:
  • Hasib Mansur

    (Biological and Agricultural Engineering (BAE), Kansas State University, Manhattan, KS 66506, USA)

  • Manoj Gadhwal

    (Biological and Agricultural Engineering (BAE), Kansas State University, Manhattan, KS 66506, USA)

  • John Eric Abon

    (Biological and Agricultural Engineering (BAE), Kansas State University, Manhattan, KS 66506, USA)

  • Daniel Flippo

    (Biological and Agricultural Engineering (BAE), Kansas State University, Manhattan, KS 66506, USA)

Abstract

Mapping is fundamental to the autonomous navigation of agricultural robots, as it provides a comprehensive spatial understanding of the farming environment. Accurate maps enable robots to plan efficient routes, avoid obstacles, and precisely execute tasks such as planting, spraying, and harvesting. Row crop navigation presents unique challenges, and mapping plays a crucial role in optimizing routes and avoiding obstacles in coverage path planning (CPP), which is essential for efficient agricultural operations. This study proposes a simple method for using Unmanned Aerial Vehicles (UAVs) to create maps and its application to row crop navigation. A case study is presented to demonstrate the method’s viability and illustrate how the resulting map can be applied in agricultural scenarios. This study focused on two major row crops, namely corn and soybean, but the results indicate that map creation is feasible when the inter-row spaces are not obscured by canopy cover from the adjacent rows. Although the study did not apply the map in a real-world scenario, it offers valuable insights for guiding future research.

Suggested Citation

  • Hasib Mansur & Manoj Gadhwal & John Eric Abon & Daniel Flippo, 2025. "Mapping for Autonomous Navigation of Agricultural Robots Through Crop Rows Using UAV," Agriculture, MDPI, vol. 15(8), pages 1-14, April.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:8:p:882-:d:1637324
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/15/8/882/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/15/8/882/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Barnes, A.P. & Soto, I. & Eory, V. & Beck, B. & Balafoutis, A. & Sánchez, B. & Vangeyte, J. & Fountas, S. & van der Wal, T. & Gómez-Barbero, M., 2019. "Exploring the adoption of precision agricultural technologies: A cross regional study of EU farmers," Land Use Policy, Elsevier, vol. 80(C), pages 163-174.
    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. Bentivoglio, Deborah & Bucci, Giorgia & Belletti, Matteo & Finco, Adele, 2022. "A theoretical framework on network’s dynamics for precision agriculture technologies adoption," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 60(4), January.
    2. Antonino Galati & Giuseppina Migliore & Alkis Thrassou & Giorgio Schifani & Giuseppina Rizzo & Nino Adamashvili & Maria Crescimanno, 2023. "Consumers’ Willingness to Pay for Agri-Food Products Delivered with Electric Vehicles in the Short Supply Chains," FIIB Business Review, , vol. 12(2), pages 193-207, June.
    3. Vecchio, Yari & De Rosa, Marcello & Adinolfi, Felice & Bartoli, Luca & Masi, Margherita, 2020. "Adoption of precision farming tools: A context-related analysis," Land Use Policy, Elsevier, vol. 94(C).
    4. Shang, Linmei & Heckelei, Thomas & Gerullis, Maria K. & Börner, Jan & Rasch, Sebastian, 2021. "Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction," Agricultural Systems, Elsevier, vol. 190(C).
    5. Kolady, Deepthi E. & Van Der Sluis, Evert, 2021. "Adoption Determinants of Precision Agriculture Technologies and Conservation Agriculture: Evidence from South Dakota," Western Economics Forum, Western Agricultural Economics Association, vol. 19(2), December.
    6. Shang, Linmei & Heckelei, Thomas & Börner, Jan & Rasch, Sebastian, 2020. "Adoption and Diffusion of Digital Farming Technologies – Integrating Farm-Level Evidence and System-Level Interaction," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305586, German Association of Agricultural Economists (GEWISOLA).
    7. Balaine, Lorraine & Dillon, Emma J. & Läpple, Doris & Lynch, John, 2020. "Can technology help achieve sustainable intensification? Evidence from milk recording on Irish dairy farms," Land Use Policy, Elsevier, vol. 92(C).
    8. J Blasch & B van der Kroon & P van Beukering & R Munster & S Fabiani & P Nino & S Vanino, 2022. "Farmer preferences for adopting precision farming technologies: a case study from Italy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(1), pages 33-81.
    9. Osrof, Hazem Yusuf & Tan, Cheng Ling & Angappa, Gunasekaran & Yeo, Sook Fern & Tan, Kim Hua, 2023. "Adoption of smart farming technologies in field operations: A systematic review and future research agenda," Technology in Society, Elsevier, vol. 75(C).
    10. Yatribi Taoufik, 2020. "Factors Affecting Precision Agriculture Adoption: A Systematic Litterature Review," Economics, Sciendo, vol. 8(2), pages 103-121, December.
    11. Margherita Masi & Marcello Rosa & Yari Vecchio & Luca Bartoli & Felice Adinolfi, 2022. "The long way to innovation adoption: insights from precision agriculture," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-17, December.
    12. Auci, Sabrina & Pronti, Andrea, 2023. "Irrigation technology adaptation for a sustainable agriculture: A panel endogenous switching analysis on the Italian farmland productivity," Resource and Energy Economics, Elsevier, vol. 74(C).
    13. Robert Finger, 2023. "Digital innovations for sustainable and resilient agricultural systems," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(4), pages 1277-1309.
    14. Ingram, Julie & Maye, Damian & Bailye, Clive & Barnes, Andrew & Bear, Christopher & Bell, Matthew & Cutress, David & Davies, Lynfa & de Boon, Auvikki & Dinnie, Liz & Gairdner, Julian & Hafferty, Caitl, 2022. "What are the priority research questions for digital agriculture?," Land Use Policy, Elsevier, vol. 114(C).
    15. Schnebelin, Éléonore, 2022. "Linking the diversity of ecologisation models to farmers' digital use profiles," Ecological Economics, Elsevier, vol. 196(C).
    16. Oksana Hrynevych & Miguel Blanco Canto & Mercedes Jiménez García, 2022. "Tendencies of Precision Agriculture in Ukraine: Disruptive Smart Farming Tools as Cooperation Drivers," Agriculture, MDPI, vol. 12(5), pages 1-15, May.
    17. Magor Ors KOLLO & Vincentiu-Andrei VERES & Maria MORTAN, 2025. "From Perception to Practice: Drone Technology in Romanian Agriculture," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 10(1), pages 5-21, February.
    18. Emily Duncan & Alesandros Glaros & Dennis Z. Ross & Eric Nost, 2021. "New but for whom? Discourses of innovation in precision agriculture," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(4), pages 1181-1199, December.
    19. Herdis Herdiansyah & Ernoiz Antriyandarti & Amrina Rosyada & Nor Isnaeni Dwi Arista & Tri Edhi Budhi Soesilo & Ninin Ernawati, 2023. "Evaluation of Conventional and Mechanization Methods towards Precision Agriculture in Indonesia," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    20. Alfons Weersink & Murray Fulton, 2020. "Limits to Profit Maximization as a Guide to Behavior Change," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 67-79, March.

    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:15:y:2025:i:8:p:882-:d:1637324. 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.