The popularity of Unmanned Aerial Vehicles or UAVs has exploded in just a few years. That’s the result of smaller, cheaper computers that allow these vehicles to fly unaided, better radio communication systems and more efficient, lighter motors for longer flight times.
As a result, UAVs are extraordinarilly capable. The flying machines available in any toyshop for a few hundred dollars would have been the envy of any UAV research team just ten years ago.
But there are still limits to what these machines can do and one of them is tracking objects on the ground. Send up one of these cheap UAVs to circle your house or to follow a car and it’ll be hopelessly lost in seconds.
That’s because object recognition tends to be a computationally intensive task and there are obvious power and weight limits for small flyers.
The standard way to solve this problem is to broadcast the images back to the ground where they can be crunched relatively easily and then sent back. But this obviously doesn’t work when communications systems are disrupted.
So today Ashraf Qadir and pals at the University of North Dakota in Grand Forks reveal a solution. With Department of Defense funding, these guys have built their own image processing machine, which is small and light enough to be carried by a small UAV. They say their device is capable of tracking objects such as cars and houses in real time without the need for number crunching on the ground.