Unmanned vehicles, including UAVs (unmanned aerial vehicles), UUVs (unmanned underwater vehicles) and UGVs (unmanned ground vehicles), will utilise a wide range of instruments and sensors to enhance the operation of the vehicle or to gather data. Unmanned vehicles are ideal remote sensing platforms for many applications, including military, industrial, surveying and environmental monitoring, due to their lower cost of operation compared to manned vehicles and their ability to thrive in hostile or hard-to-reach environments.
Unmanned vehicles with large fuel tanks, particularly larger UAVs, may require sensors to monitor the level and flow rate of the fuel. State-of-the-art UAV sensor technologies include ultrasonic fuel flow sensors and capacitive fuel level sensors, both of which use no moving parts and are ideal for the harsh high-vibration conditions found in UAV applications.
UAV sensors also include Inertial Measurement Units (IMUs), which fuse together information from different sensors such as gyroscopes, accelerometers and magnetometers to provide measurements that can be used to calculate orientation and velocity of the UAV. This data can be combined with another source of information such as a GPS to further increase the accuracy of the calculations.
LiDAR (Light Detection and Ranging) sensors, which measure the reflection time of a pulsed laser beam, have a variety of uses in unmanned systems. They may be used for navigation and collision avoidance by UAVs and autonomous driving systems, as well as for mapping and other imaging applications such as agricultural and forestry surveying. LiDAR provides an alternative to traditional photogrammetry methods for when the mapped area contains many obstructions.
Other imaging sensors that may be mounted on unmanned vehicles and UAVs include thermal imaging for building inspection, search & rescue and security, as well as other electro-optical (EO) sensors that operate in the visible spectrum. Hyperspectral precision agriculture UAV sensors measure reflected light to provide data on the health of crops, allowing farmers to optimize application of pesticides and fertilizers and maximise crop yields.