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Aerial Robotics for Precision Agriculture: Weeds Detection Through UAV and Machine Vision

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Abstract

In this chapter, the authors touch upon the problem of weeds detection. In particular, a real-life problem of Hogweed of Sosnowski (lat. Heracleum) detection using intelligent aerial robotics is considered. Until now, this challenge has not been fully addressed—it requires further research activities for designing a novel monitoring platform with intelligent capabilities on board allowing for the automation of weed detection routine which is currently carried out manually. The detection task imposes several challenges: (i) detection, without human presence, should be carried out in order to prevent the seeds dissemination, (ii) monitoring is required to cover a wide range, and (iii) the location of the data should be accessible and “real time” for fast action of the findings on the data analysis. To address this problem, the authors discuss the following points: relevant unmanned aerial vehicle (UAV) architecture, the corresponding image capture cameras, computer vision methods, and computer vision hardware for UAV.

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  1. Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia

    Alexander Menshchikov & Andrey Somov

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  1. Alexander Menshchikov
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  2. Andrey Somov
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Correspondence to Andrey Somov .

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  1. Universidad Autónoma de Baja California, Mexicali, Baja California, Mexico

    Oleg Sergiyenko

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Menshchikov, A., Somov, A. (2022). Aerial Robotics for Precision Agriculture: Weeds Detection Through UAV and Machine Vision. In: Sergiyenko, O. (eds) Optoelectronic Devices in Robotic Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-09791-1_2

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