Nowadays most medium to higher end consumer drones come with some sort of obstacle avoidance. Consumer drone manufacturers such as Skydio 2, DJI and Autel Robotics all feature it but it typically takes from 20 to 40 milliseconds for the drone to process the image and react. That may seem quick, but it is not quick enough to avoid a bird or another drone, or even a static obstacle when the drone itself is flying at high speed. This can be a problem when drones are used in unpredictable environments, or when there are many of them flying in the same area.
The Skydio 2 for instances touts visual sensing. Everything the autonomy engine does comes from processing visual data. In addition to the user camera, the Skydio 2 has 45 megapixels of visual sensing with six 4K navigation cameras, each of which has a super-fisheye lens with a 200° field-of-view. Three of the navigation cameras are pointed up and three are pointed down, so not only can Skydio 2 see in every direction at once, it’s got triple coverage to minimize the chance of missing anything, according to Skydio’s website. The most popular manufacturer of consumer drones, DJI, uses “Omnidirectional Obstacle Sensing” on its widely popular Mavic 2 series (Zoom and Pro) which includes left/right, up/down, and forward/backward obstacle sensing. Unlike Skydio 2‘s obstacle avoidance, the Mavic 2′s “Omnidirectional Obstacle Sensing” does not fully cover the circumference of a 360-degree arc and the left and right obstacle sensing system only works in specific modes and environments.
In order to solve this problem, researchers at the University of Zurich have equipped a drone with special cameras and algorithms that reduced its reaction time down to a few milliseconds – enough to avoid a ball thrown at it from a short distance. The results, published in the journal Science Robotics, can make drones more effective in situations such as the aftermath of a natural disaster.
“For search and rescue applications, such as after an earthquake, time is very critical, so we need drones that can navigate as fast as possible in order to accomplish more within their limited battery life,” explains Davide Scaramuzza, who leads the Robotics and Perception Group at the University of Zurich as well as the NCCR Robotics Search and Rescue Grand Challenge. “However, by navigating fast drones are also more exposed to the risk of colliding with obstacles, and even more if these are moving. We realized that a novel type of camera, called Event Camera, are a perfect fit for this purpose”.
According to Scaramuzza, “One day drones will be used for a large variety of applications, such as delivery of goods, transportation of people, aerial filmography and, of course, search and rescue,” he says. “But enabling robots to perceive and make decision faster can be a game changer for also for other domains where reliably detecting incoming obstacles plays a crucial role, such as automotive, good delivery, transportation, mining, and remote inspection with robots”.