To improve reaction times, the researchers equipped a drone with what’s known as an event camera. Your typical video camera relies on a sensor that exposes all of its pixel elements at the same time before sending them along to be processed; objects can only be detected by algorithms once an entire frame—and often multiple frames—have been analyzed. That’s what contributes to the delays in reaction times. An event camera, by comparison, has pixels that are individually “smart” and only pass along data to be processed when a change in what they’re seeing has been detected. If they don’t see anything new, they remain silent, allowing algorithms and processors to focus their efforts on pixels that have detected an approaching obstacle, which speeds up the entire process.

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The UZH researchers developed their own custom algorithms that are able to recognize threats detected by the event camera after sampling footage from a very short amount of time, while taking into account the speed and direction of the drone itself. The results are reaction times reduced down to just 3.5 milliseconds, making a drone far more effective at dodging a fast-moving obstacle.

It’s an improvement, but not perfect just yet. From their testing, the researchers found a drone equipped with the new vision system could dodge a large ball thrown from three meters away at a speed of about 22 miles per hour more than 90 percent of the time. Knowing the size of the incoming object ahead of time helped improve the results, but in the field a pair of event cameras on the drone, generating stereoscopic images, could allow them the craft to calculate the size of a threat all on its own. It can’t be used to dodge bullets just yet, but the current improvements in reaction times will allow autonomous drones to fly 10 times faster than they can now, meaning you potentially won’t have to wait as long for your drone-delivered pizza to arrive.