The National Research Council of Canada (NRC) has developed cutting-edge technology that could prevent drones colliding with airplanes.
With unmanned aerial vehicles (UAV) becoming increasingly popular, the risk of collision with manned aircraft has become a concern. To integrate UAVs into the national airspace, the National Research Council of Canada (NRC) has developed its latest cutting-edge technology in the form of the Passive Intelligent Collision Avoidance Sensor (PICAS) system, which allows unmanned aircraft to detect oncoming aircraft more accurately than ever before in order to avoid collisions and enhance safety.
PICAS was created to fill a “crucial technology and safety gap,” the researchers say. It allows unmanned vehicles/drones to detect aircraft that are not able to communicate their position to other aircraft.
How it works
“In sense and avoid, the hard problem is the sensing problem. You want to detect aircraft at long ranges and you also want a package that is light and low-power that can go on a UAV. This is exactly what we are working to create with PICAS,” said Dr. Cyrus Minwalla, Research Officer in Airborne Research at the NRC.
PICAS uses cameras that have a large field of view while also having a microscope-like capability that can “see” oncoming objects at long ranges. The PICAS software algorithm is then able to examine the images and determine if the object is another aircraft on a collision course with the UAV. This ability is unique because it can detect an aircraft that is approaching head on while it is still far enough away for the UAV to avoid. It is able to sense, in real time, Cessna-sized collision-course targets at a distance of up to eight kilometres. The box-like sensor is also small enough to be attached to the exterior of an unmanned vehicle.
As of yet, there is no such technology that is commercially available. Flight tests are currently being conducted to verify PICAS’ accuracy, putting the NRC on course to make the first commercially viable sense and avoid system by 2018.
