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Artificial intelligence and machine learning for unmanned vehicles

A U-2 Dragon Lady assigned to the 9th Reconnaissance Wing prepares to land at Beale Air Force Base, Calif., after artificial intelligence took flight aboard a military aircraft.

NASHUA, N.H. – What was once the realm science fiction writers is growing as unmanned vehicles are given more capability for autonomous decision making thanks to improvements in artificial intelligence (AI) and machine learning, Military & Aerospace Electronics reports. Continue reading original article.

The Intelligent Aerospace take:

April 27, 2021 – First, unmanned aerial vehicles (UAVs) took to the skies. In fact, the British military developed the first radio-controlled unmanned aircraft during World War I — a scant 14 years after the Wright Brothers’ first flight in 1903. UAVs really came into their own during the Vietnam War and have become even more prevalent and essential since then.

As UAVs proved themselves more invaluable over the years, the Department of Defense (DOD) asked industry experts to bring the unmanned revolution down to Earth in the form of unmanned ground vehicles (UGVs) and even to the seas with unmanned underwater vehicles (UUVs).

Though each domain had unique problems to solve, the difficulty communicating from the surface to UUVs meant a greater need for machine autonomy — the ability to make decisions without direct human input — made possible with artificial intelligence (AI) and machine learning (machine learning).

Even though radio frequency (RF) and satellite communications (SATCOM) methods allow for relatively easy contact with UGVs and UAVs, the prospect of “smart” unmanned systems on the ground and in the sky also is helping drive the autonomous revolution.

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Jamie Whitney, Associate Editor
Intelligent Aerospace