Abstract
Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools in precision agriculture due to their ability to provide timely and detailed information over large agricultural areas. In this sense, this work aims to evaluate the semi-autonomous navigation capacity of a multirotor UAV when applied in the field of precision agriculture. For this, a small aircraft is used to identify and track a set of fiducial markers (Ar_Track_Alvar) in an environment that simulates inspections of insect traps in olive groves. The purpose of this marker is to provide a visual reference point for the drone’s navigation system. Once the Ar_Track_Alvar marker is detected, the robot will receive navigation information based on the marker’s position to approach the specific trap. The experimental setup evaluated the computer vision algorithm applied to the UAV to make it recognize the Ar_Track_Alvar marker and then reach the trap efficiently. Experimental tests were conducted in a indoor and outdoor environment using DJI Tello. The results demonstrated the feasibility of applying these fiducial markers as a solution for the UAV’s navigation in this proposed scenario.
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Acknowledgments
The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020), SusTEC (LA/P/0007/2021), Oleachain “Skills for sustainability and innovation in the value chain of traditional olive groves in the Northern Interior of Portugal” (Norte06-3559-FSE-000188), Centro Federal de Educação Tecnológica Celso Suckow da Fonseca (CEFET/RJ) and Fundação de Amparo á Pesquisa do Estado do Rio de Janeiro (FAPERJ). The authors thank Marta Sofia Madureira from the Agrobio Tecnologia - Insects Laboratory, part of the Mountain Research Center (CIMO), for the technical support provided throughout this work.
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Berger, G.S. et al. (2024). UAV-Assisted Navigation for Insect Traps in Olive Groves. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-031-59167-9_8
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