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A UAV Guidance System Using Crop Row Detection and Line Follower Algorithms

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Abstract

In precision agriculture, activities such as selective spraying of agrochemicals are essential to maintaining high productivity and quality of agricultural products. The use of unmanned aerial vehicles (UAVs) to perform this activity reduces soil compaction, compared to the use of heavy machinery, and helps to reduce the waste of these artificial substances through a punctual and self-regulating application. This work proposes an entire guiding system for use on UAVs (hardware and software) based on image processing techniques. The software part consists of two algorithms. The first algorithm is the Crop Row Detection which is responsible for the correct identification of the crop rows. The second algorithm is the Line Filter that is responsible for generating the driving parameters sent to the flight controller. In the field experiments performed on the proposed hardware, the algorithm achieved a detection rate of 100% of the crop rows for images with resolutions above 320 × 240. The system performance was measured in laboratory experiments and reached 31.22 FPS for images with small resolution, 320 × 240, and 1.63 FPS for the highest resolution, 1920 × 1080. The main contribution of this work is the design and development of an entire embedded guidance system composed of a hardware and software architectures. Other contributions are: the proposed filter for the image pretreatment; the filter to remove the false positive lines; and the algorithm for generating the guiding parameters based on detected crop rows.

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Acknowledgments

The authors would like to thank for the help of the technician staff at UFRGS that contributed to this project supporting the field trials. The authors thank Marcos Vizzotto for helping with the hardware assembling. Finally, the authors thank CAPES, CNPQ, and FAPERGS for the financial support to this project.

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Authors and Affiliations

  1. Electrical Engineering Graduate Program (PPGEE), Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil

    Maik Basso & Edison Pignaton de Freitas

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  1. Maik Basso
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  2. Edison Pignaton de Freitas
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Correspondence to Maik Basso.

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Basso, M., Pignaton de Freitas, E. A UAV Guidance System Using Crop Row Detection and Line Follower Algorithms. J Intell Robot Syst 97, 605–621 (2020). https://doi.org/10.1007/s10846-019-01006-0

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  • DOI: https://doi.org/10.1007/s10846-019-01006-0

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