## 3 Obstacle Avoidance Scenario
### Detection Sensors  
Due to atmospheric conditions, such as lighting difference, temperature difference, spray drift or spray fog, water vaporization, etc., selecting the type of sensors for obstacle  
Figure 8: (**a**) Reactive control architecture; (**b**) deliberative planning architecture; (**c**) hybrid control architecture [36]. Figure 7: Obstacle avoidance scenario group. detection is an essential factor for agricultural sprayer UAV [99; 100; 101; 102]. Different kinds of sensors generate the required information about the obstacle, including their surrounding environment, for the UAV to calculate the obstacle distance and processes necessary for safe path generation around the obstacle; this information contains the size, shape, and location of the obstacles [103; 104], and according to the task requirements, different systems use various sensor setups [105]. Sensor classification can be classified into two functional axes [106]: proprioceptive/exteroceptive and passive/active. Proprioceptive sensors detect a vehicle's internal detection data, such as position, orientation, and speed, which are detected by sensors such as velocity sensors [107], tilt sensors [108], position sensors [109], heading sensors [110], accelerometers [111], etc. Exteroceptive sensors collect information and features from the surrounding environment as well as the surrounding obstacle data of the vehicle, which are obtained by sensors such as ToF [112], lidar [113], laser [114], camera [115], sonar [116], microwave radar [117], etc. These sensors provide information collected from the surroundings and help the vehicles in their decision-making and interaction with the environment. From the viewpoint of technical information, the other type of classification is passive or active. These are some different sensing systems used to detect obstacles and record information of the obstacle's presence on the path. Passive sensors use the available environmental energy sources to process data of the surroundings [106]. Sun provides energy, which has visible spectrums and creates light reflections off the objects. These visible wavelengths and reflecting lights can be detected by light- or wavelength-detecting sensors and different camera types, such as CCD, CMOS, and thermal cameras [118; 119]. That is why these kinds of sensors are often defined as vision-based sensors, which generate information based on pictures [120; 121; 122; 123; 124; 125; 126; 127; 128; 129]. On the other hand, active sensors use their own generated energy, such as light and soundwaves, and detect the energy reflections by sonar, microwave radar, laser, ToF, etc. From the reflected energy, the sensor generates the surrounding environmental reaction. Because active sensors generate information depending on their controlled interactions, sometimes its performance is better. However, the generated energy can be influenced by other sources of energy, which may cause error readings [130; 131; 132; 133; 106; 130; 107; 134; 108; 135; 136]. For agricultural UAVs in different environments, a single sensor may not fulfill the task requirements. So, in that case, a multi-sensor combination, as well as sensor fusion, can be used for better performance [137; 138]. [PERSON] et al. [139], [PERSON] et al. [140], and [PERSON] et al. [141] proposed an optical flow and stereo vision sensor fusion to improve the accuracy of the obstacle avoidance performance. [PERSON] et al. [142] presented infrared with ultrasonic sensors for obstacle avoidance at a low cost. on farmland, the obstacles and situation are different and more specified. [PERSON] et al. [143] made a datasheet of the different sensor performance types using a ground robot on farmland. After studying the Chinese agricultural UAV industry and the different types of detection sensors for obstacle avoidance, [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] [97] compared and summarized the features, advantages, and disadvantages of the sensors from the perspective of agricultural field operation.