The increasing world population makes it necessary to fight challenges such as climate change and to realize production efficiently and quickly. However, the minimum cost, maximum income, environmental pollution protection and the ability to save water and energy are all factors that should be taken into account in this process. The use of information and communication technologies (ICTs) in agriculture to meet all of these criteria serves the purpose of precision agriculture. As unmanned aerial vehicles (UAVs) can easily obtain real-time data, they have a great potential to address and optimize solutions to the problems faced by agriculture. Despite some limitations, such as the battery, load, weather conditions, etc., UAVs will be used frequently in agriculture in the future because of the valuable data that they obtain and their efficient applications. According to the known literature, UAVs have been carrying out tasks such as spraying, monitoring, yield estimation, weed detection, etc. In recent years, articles related to agricultural UAVs have been presented in journals with high impact factors. Most precision agriculture applications with UAVs occur in outdoor environments where GPS access is available, which provides more reliable control of the UAV in both manual and autonomous flights. On the other hand, there are almost no UAV-based applications in greenhouses where all-season crop production is available. This paper emphasizes this deficiency and provides a comprehensive review of the use of UAVs for agricultural tasks and highlights the importance of simultaneous localization and mapping (SLAM) for a UAV solution in the greenhouse.

The use of unmanned aerial vehicles (UAV) is increasing today. UAVs can be divided into two parts, which are remote controlled and can travel automatically due to a certain battery problem. Recent research has also focused on the development and application of new algorithms to autonomously control these vehicles and determine the shortest flight paths. Together with these researches, UAVs are used in many civil activities such as weather forecasts, environmental studies and traffic control. Three-dimensional (3D) path planning is an important issue for autonomously moving UAVs. The shortest path for Unmanned Aerial Vehicles (UAV) is determined by using two-dimensional (2D) path planning algorithms using the obstacles in the environment, and allows UAVs to perform their environmental tasks as soon as possible. The purpose of this study is to determine the shortest path to the target point and avoiding obstacles for UAVs using the Dijkstra algorithm. It was developed to evaluate the arrival time of the UAVs in the path planning algorithm with the simulation performed in the MATLAB program. In this study, the obstacles were defined for the purpose of the building with different heights and different widths and 2D and 3D models were carried out, assuming that the UAV flies at certain heights. In addition, the flight of the UAVs in the route planning determined in the real applications was carried out and the data such as battery consumption, amount of battery spent, speed, amount of travel were examined.