## 2 Literature Review  
### Unmanned Aerial Robots' Applications in Agriculture  
IoT and similar technologies such as WSN, which have become popular in recent years, are used to meet the needs in the agriculture fields. Along with the IoT, the widespread use of autonomous robots such as Unmanned Aerial Robots (UAVs) increases productivity in agriculture. In recent years, studies related to this subject have gained acceleration [21; 22; 23; 24]. In [25], the authors used UAVs to detect possible drainage pipes. Often, farmers need to repair or construct drain lines to efficiently remove water from soil. Therefore, in this study, they wanted to increase resource consumption and productivity in agriculture by focusing on this issue. In [26], the combined application of UAV and Unmanned Ground Robot (UGV) was proposed to monitor and manage crops. The authors proposed a system that can periodically monitor the condition of crops, capture multiple images of them, and determine the state of the crops. In addition to many UAV-based studies and products, recently, the concepts of IoT and autonomous robots have begun to be presented together. In this way, the data detected by the UAVs or each autonomous robot reach the place where they need to be sent instantly, the necessary actions can be taken on this data, and it can quickly provide a decision mechanism to the farmer or other technological devices. For example, in [27], the authors presented a farm monitoring system via UAV, IoT, and Long-Range Wide Area Network (LoRAWAN) technologies for efficient resource management and data delivery. In this regard, they monitored water quality. In [28], the authors proposed a new model to minimize the post-disaster inspection cost to serve a disaster-affected area. In this study, battery charging costs, service costs, drone hovering, turning, acceleration, cruise, and deceleration costs were considered. In this regard, the authors used two heuristics (_not meta-heuristics_) algorithms, but it was not possible to avoid the fundamental problems of heuristics [19]. In [29], the study aimed to deliver to a number of customers by UAVs, namely drones. Here, it focused on three issues. One was the launch points of the drones, the second was the launch points of the customers, and the third was the distance between the customer and the drone. The proposed method goal was to minimize the total operational cost, including an explicit calculation of the energy consumption of the drone as a function of the drone speed. The most common role of drones in agriculture is to assess and monitor crops. For this, remote sensing is carried out, but this task is not enough when agricultural applications become more widespread. For this, autonomous mobile robots such as drones and other UAVs with technologically different features are designed for various agricultural purposes. In [30], the authors used satellite images to crop mapping. They used the remote sensing feature and utilized advantages of combined radar data and optical images to identify the type of crops. The authors claim that this combination provides an increased chance of examining details and provides more reliable information compared to a single-sensor classification method. We can generally categorize UAV/drone-based agricultural applications into three categories: Monitoring Applications, (b) Spraying Applications, and (c) Multi-robots Applications. In the first category, crops are tracked, and certain appropriate information and vegetation indices are extracted. For this, it is necessary to provide the imaging data that are processed later. Thus, we can identify problem areas in the crop that suffer from various diseases and pests. The data received by UAVs sensors can be characterized based on their spectral, spatial, and temporal properties. The selection of suitable sensors and data depends on the nature of their applications. There are many studies in the literature related to this [31; 32; 33].