When you’re zipping through the air at 60 kilometres per hour, it can be hard to work out where you’re going. But now drones can create detailed 3D maps as they fly – an advance that could let them navigate the world free from human input.
Called Hydra Fusion, the system could one day allow drones to use a form of navigation known as simultaneous localisation and mapping to find their way in unfamiliar spaces – just as some robots do on the ground. It will also make them better at aerial surveillance.
Hydra Fusion works by stitching together multiple images – in this case, consecutive frames of footage from a drone’s video camera – to form a detailed 3D map while it is in the air. “We can fly a drone along at 30 knots and create a map as we go,” says John Molberg at Lockheed Martin, part of the team behind the system.
It previously took hours of postflight processing to build maps from drone footage. The bottleneck was processing power. The team overcame this by harnessing the power of GPUs – fast image-processing chips originally developed for games.
At 60 kilometres per hour, Hydra Fusion creates maps with a resolution of 30 centimetres per pixel, clearly showing trees and buildings (see picture, left). Higher resolutions – up to 2.5 cm per pixel – can be generated at slower speeds and low altitudes. Even greater detail may be possible: for one client, Lockheed Martin is looking into mapping changes as small as 6 millimetres in the position of railway tracks. David Hambling
It feels like there’s a drone for every occasion: one to monitor farms, one to spy on wildlife, yet another to deliver your pizza. Now a drone called Teal aims to do it all – thanks to a boost in brainpower.
“Image recognition is used in one app that lets you instruct the drone to follow a specific person“
Most drones are designed with a specific use in mind, says George Matus, CEO of iDrone in Salt Lake City. “We’re making this almost like a smartphone for drones, where we can build an app store around it.”
Matus has been flying drones since he was 11 years old. “I built this wish list of everything I wanted in a drone,” he says.
Now 18, he has developed Teal, a drone that can make decisions in the air. That’s thanks to brain-inspired software from Neurala, a robotics firm in Cambridge, Massachusetts, that has previously developed tech to guide space rovers.
Layers of artificial neural networks handle different tasks, such as interpreting what the camera sees or choosing where the drone will go next.
“The Teal drone is the first drone with a processor powerful enough for us to run our machine learning software right on the drone itself, so it can make immediate decisions,” says Roger Matus, vice president at Neurala. “It’s the first stage of autonomous flight.”
Neurala’s image recognition is used in one of Teal’s three built-in apps, which lets you instruct the drone to track a specific person. Over time, the team intends to develop skills like better obstacle avoidance and autonomous navigation.
Teal’s two other starter apps offer flight control and a racing game. George Matus hopes developers will build on the drone’s smarts to create more, such as a search-and-rescue function, or one that learns when the drone is about to crash and instructs it to take avoidance action. Aviva Rutkin
Why have one when you can have a swarm? Getting multiple drones to carry out a coordinated task means that more ground can be covered in less time. It took a drone swarm just 6 hours to map the Matterhorn mountain in the Alps, for example.
Moving about as a swarm is tricky, however. Single drones can avoid obstacles with relative ease, but it is hard to do so while flying in formation.
Into the woods
So Matthias Brust at the Singapore University of Technology and Design and Bogdan Strimbu at Oregon State University devised a way for drones to stick together as they fly through one of the toughest environments they could think of – a forest. Getting a drone swarm to pick its way through trees means that such swarms could soon map and take pictures of areas that were previously off limits.
Their method is based on a follow-the-leader approach. A lead drone is given a GPS destination, and the rest of the pack maintains its position relative to the leader, while avoiding obstacles. If the leader runs low on battery or crashes, the swarm picks a new captain on the fly.
Because trees and leaves – or buildings in a city – can block the swarm’s communication with the ground base, the lead drone collects data from its teammates and periodically rises above the canopy to send images back home.
The researchers tested their system by running a computer simulation in which eight drones approached a tree and took up positions to scan it. The swarm reached its destination and spread out almost as quickly as it took a single drone to arrive there. If the drones can surround a tree without crashing, flying past many trees shouldn’t be a problem, says Brust.
Chris Lippitt at the University of New Mexico looks forward to drone swarms soon mapping hard-to-reach places. “It really changes the equation for how we can measure the environment,” he says. Conor Gearin
This article appeared in print under the headline “Drones find their way”
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