Researchers Develop Drone that Shoots Darts for Environmental Monitoring
Recently, researchers from Imperial College London have created a drone that can shoot sensor-containing darts at trees for environmental monitoring purposes. What technologies are drones reliant on, why is a dart-shooting drone useful for environmental monitoring, and how will AI systems allow for future sensor missions with drones?
What is drone technology?
When speaking about drones in today’s world, most people think of small quadcopter designs often sold as a toy which are becoming smaller and cheaper every day while others may think of drones used by companies such as Amazon who are hoping to make drone delivery mainstream. However, it was not long ago when the term drone carried a large amount of negativity due to the large-scale use of unmanned aerial vehicles (UAV), in military applications. But even then, drones go back as far as the first world war with the development of small unmanned planes that could be radio-controlled to take on the mammoths of the skies, the Zeppelin.
Modern drones are only possible due to the leaps and bounds made in miniaturising electronics. While drones may seem to be a product of modern technology, the processing power and circuitry needed to make a drone work is far simpler than you may realise. Unlike remote-controlled planes and helicopters, drones that utilise a quadcopter design require motor controllers for each motor, and the use of a gyroscope allows for the quadcopter to determine its yaw, pitch, and roll. From there, a PID controller can be used in combination with the four motors to keep the system balanced. Additional controllers can be included to measure the altitude and increase/decrease power to all motors to adjust the altitude accordingly. All of these features can be executed on a wide range of entry-level microcontrollers which all have been available for the past two decades. What has made modern drones possible besides the miniaturisation of circuitry is the development of Lithium-based battery technologies. Such batteries have incredibly large energy densities which allow for them to be reduced in size, and thus also in weight. At the same time, motor technology has allowed for incredibly small, but high RPM motors and the result of all of this is the possibility for small, lightweight drones.
Researchers Develop Drone Shooting Dart
Recently, researchers from the Imperial College London have developed a drone that can shoot darts with a high degree of accuracy. The drone system, which is currently manually piloted, carries a mechanical launching mechanism utilising a compressed spring for energy storage and a shape memory alloy spring as the release mechanism. When current is applied to the shape memory alloy spring, the spring changes shape, and this releases the hook that keeps the mainspring compressed. From there, a 30-gram dart can be accurately fired up to 4 meters with an accuracy rate as high as 90% (some tests showed 100%, but this may be for distance up to 1 meter). The drone developed by the researchers can be used for up to 17 shots on a single charge, while the darts themselves integrate sensors to create a wireless sensor network (WSN), for use in remote monitoring of environments.
According to the researchers, the use of darts over other technologies allows for sensors to be accurately positioned. Other technologies, such as drop placement of sensors or the use of adhesives, are not as reliable and can create unpredictable sensor networks. The use of darts to monitor environments in wooded areas also keeps sensors off the ground, which may become damaged by flooding, animals, and plant growth. The use of drones in such environments also removes the danger of climbing trees by researchers when deploying such networks, and drones allow for researchers to access areas that pose other danger risks such as beehives and wasps nests.
How will AI and ML change drone technology in the future?
While the drones demonstrated by the researchers demonstrate their practical use in extreme environments, they are still required to be piloted by an operator. Using human pilots, in general, is preferred over an AI system, but when operating in tight spaces, an AI may be preferable. The first advantage to an AI piloting the drone is the speed at which AI can operate and react to sudden changes. Unlike human pilots, AI can have a 360-degree vision and simultaneously observe all sensory data from all angles. This means that a human pilot may not notice branches behind a drone, but an AI would be aware of all branches around it (assuming it has correctly identified them). From there, an AI would be able to manoeuvre the drone into the optimum deployment position properly, and carefully move the drone out of the area. The use of automated drones also allows for large networks to be quickly established, while researchers can focus on configuring sensors and reading data from the network.