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Get a daily digest of the latest news in tech, science, and technology, delivered right to your mailbox. Subscribe now.Going forward, there will likely be a significant rise in the amount of autonomous drone aircraft operating in uncontrolled airspace beneath 400 feet of altitude. By 2027, experts predict that the US will have a fleet of around 1 million commercial UAS doing duties, including package delivery, traffic monitoring, and emergency aid.
Aiming to find a practical solution, a team of researchers at the Johns Hopkins Institute for Assured Autonomy has utilized artificial intelligence to construct a system that might more safely coordinate drone traffic in the future. Their work involved substituting some human-in-the-loop operations with autonomous decision-making to help it scale according to expected demand. has already taken note and plans to develop a system to control the designated airspace below 400 ft.
The researchers added two more realistic features to their model. The system is made more adaptive by "noisy sensors" that simulate the unpredictability of real-world settings. A "fuzzy interference system" also determines the danger level for each drone depending on variables, including closeness to obstacles and adherence to the intended path. According to the team, these techniques provide the system with the ability to make judgments on its own to avoid accidents.
"Our study considered a variety of variables, including scenarios that involve 'rogue drones' that deviated from their planned routes. The results are very promising," said Louis Whitcomb, a professor of mechanical engineering at the Whiting School of Engineering and a researcher at the Institute for Assured Autonomy.
Going forward, for a more accurate portrayal, the team intends to improve its simulations by adding dynamic barriers like weather and other real-world elements.
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