*2.3.3 LiDAR*

It calculates distances and detects objects by measuring the time, it takes for a short laser pulse to travel from the sensor to an object and back using the known speed of light [9]. Laser sensors mainly used in autonomous navigation require optical systems thereby making them unsuitable for liquid, the dusty and smoky farming environments in addition to their weight and production cost, especially for small (sUAV) and micro unmanned aerial vehicles (MAVs). 3D scanning information takes so much time with laser scanners that make them unsatisfactory for real-time obstacle avoidance [26]. However, Huang et al. [5] proffered that light detection and ranging (LiDAR) optical sensor could be configured in a multi-sensor platform for agricultural field survey and crop height profiling.

#### *2.3.4 Infrared (IR)*

This sensing technology is based on the principle of triangulation whereby the infrared emitter emits an infrared beam at a certain angle and the light is reflected back on encountering the object. On detection, the object distance is calculated [18]. Output on analogue voltage corresponds to the distance to the reflecting object [15]. It works under all weather conditions including a night to measure distances and describe contours. It must, however, avoid direct sunlight and reflections to evade interference or failure of the OA system [6]. Corrigan [15], however, noted that IR obstacle avoidance sensors work with a specific frequency of infrared produced by the emitter to prevent them from being confused by visible light. Its good concealment and all-time service confer it with unique ability to observe animals in their natural habitats without causing disturbances [9]. On his part, Wang et al. [12] argued that the detection distance is small and the light emitted by the system is easily disturbed by the external environment.

#### *2.3.5 Line structured light*

It is emitted from the laser and converged into the light band of different shapes after passing through different lens structures [6]. Through the image acquisition,

processing and calculation, the distance, azimuth and width and other parameter information of front obstacles are extracted [24]. Single camera-based obstacle avoidance systems use structured light to map their environment in 3D without being weighed down by traditional bulky LiDAR [25]. Wang et al. [6] however observed that there are mutual interferences between adjacent structural light sensors with natural light nullifying structured light for the outdoor environment and hence not commonly used in agricultural UAVs.
