Mine clearance processes are accelerating and safety is increasing with drones equipped with artificial intelligence and advanced sensors. Here are the details of the new technology and test results:
AI-powered drones are ushering in a new era in mine clearance processes. Multi-week tests conducted by the British Army and the Defence Science and Technology Laboratory (Dstl) revealed that unmanned aerial vehicles can detect widespread mines and unexploded ordnance faster and more safely. These studies, carried out in Essex, aim to identify risks on the ground before soldiers directly enter dangerous areas.
Multi-Layer Detection System with Advanced Sensors and Artificial Intelligence
The problem of mines and unexploded ordnance stands out as one of the most complex and risky aspects of military operations in modern battlefields. For example, following Russia's invasion of Ukraine, it is estimated that approximately 174,000 square kilometers, or about 30 percent of the country's total area, may be contaminated with mines and ordnance. This situation directly affects not only military progress but also civilian life and reconstruction efforts. Similar problems have been ongoing for many years in conflict zones like Syria and Afghanistan.
The new approach developed to counter this challenging situation significantly differs from traditional mine clearance methods. Systems developed under the UK's Ground Area Reconnaissance and Assurance Project (GARA) are based on a three-stage operational process on the ground. The first stage involves detection and classification by drones. Subsequently, threats are marked and prioritized using the collected data. The final stage involves neutralization through robotic systems, explosive-deploying unmanned vehicles, or, when necessary, human intervention.
The quadcopter drones used in the tests are equipped with optical and thermal cameras, as well as long-wave infrared sensors, magnetometers, and advanced computer vision algorithms. This sensor combination facilitates the detection of different types of ordnance, providing a significant advantage, especially in identifying non-metallic or plastic-cased mines.
On the artificial intelligence front, continuous learning capability stands out. The system is designed to be quickly retrained with new data from the field. Operators can introduce new types of detected threats to the system, thereby increasing the algorithm's accuracy. This structure creates a reconnaissance layer between the human operator and the digital system. Data collected by drones is transmitted to remote military personnel, allowing for the creation of a detailed risk map before entering the field. This significantly reduces the risk faced by explosive ordnance disposal teams and shortens operation times, enabling faster clearance of large areas.
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