Abstract
By 2050, growth population worldwide will demand a great amount of resources, specially in agricultural sector. In order to supply such resources, farmers will need advance tools and techniques to improve the efficiency along all farming processes e.g. precision farming, Unmanned Vehicles Systems (UVS). This paper shows the simulation results of an algorithm developed to perform the path planning process for Unmanned Aerial Vehicles (UAVs) autonomously, in agricultural environments. The aim of this project is to automate such process and provide the appropriate conditions to execute further supervision activities. The algorithm takes into account photogrammetric parameters such as the ground sample distance (GSD) and the overlap between photos. Image processing techniques are implemented to identify the crop boundary and rows’ orientation. The project was developed using open-source tools such as OpenCV, ROS and Gazebo. The paths generated by this algorithm allow the UAV not only to go across the identified crop following the row orientation, but also to guarantee the desired resolution, specified by the GSD.
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Palomino-Suarez, D., Pérez-Ruiz, A. (2020). Towards Automatic UAV Path Planning in Agriculture Oversight Activities. In: Martínez, A., Moreno, H., Carrera, I., Campos, A., Baca, J. (eds) Advances in Automation and Robotics Research. LACAR 2019. Lecture Notes in Networks and Systems, vol 112. Springer, Cham. https://doi.org/10.1007/978-3-030-40309-6_3
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