by DAVID AXE
One of the biggest challenges in the world of Unmanned Aerial Vehicles is how to get them to fly together, in formations or “swarms,” cooperating and not colliding. Developers are testing out a number of methods: proximity-detecting radars and lasers, computer models that treat each drone like a node in network, etc. But so far, nobody’s come up with something that is cheap and reliable enough for everyday use.
Or maybe someone has. Richard Wagner, an aerospace engineer, wrote me recently to describe a project he worked on nearly 20 years ago, during the early days of modern UAVs. It was called Sensor-Driven Airborne Replanner, or SDAR. “The SDAR system was capable of the kinds of behaviors that you describe in your article,” Wagner said. “While for our mission it was outfitted with either an E/O or infrared camera and a direction-finding radio receiver as its main mission sensors, outfitted with another sensor suite, it could easily fly formation, see and avoid other objects (including aircraft), or allow multiple aircraft to operate cooperatively.”
Wagner worked on the Navy-funded project between 1989 and 1992 at Naval Air Development Center in Warminster, Pennsylvania. “To my knowledge, the abilities of the SDAR system have not been matched by any other system to date.”
The key is to keep it simple, Wagner wrote in a paper published at the end of his project. Unlike most later drones, SDAR didn’t remain in constant contact with a ground station, in order to avoid the problem of enemy eavesdroppers or jamming, the paper explained. Instead, the robot was fully autonomous, and either beamed back sensor data in quick bursts, or stored it for download once it had returned to base. The craft navigated by pre-set GPS waypoints, and maneuvered and investigated objects — ships, especially — by using what Wagner called “sensor cross-cueing,” “where one sensor is used to direct another to a subject of interest.”
That kind of sensor teamwork could allow a drone to detect other drones and keep its distance.
“Since the time of SDAR’s development,” Wagner said, “I’ve watched team after team approaching this problem with complex solutions that have kept them from achieving their goals.”
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