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DroNet uses deep machine learning for autonomous flight, a labor union takes a stand on package delivery by drone, a tiny radar for sUAS, counter-unmanned aerial systems, and a British drone survey.

UAV News

AI-Powered Drone Mimics Cars and Bikes to Navigate Through City Streets

Researchers have developed a drone that can autonomously fly through the streets of a city. DroNet uses minimal onboard sensing and is trained with datasets collected by cars and bicycles.

Two years ago, roboticists at the University of Zurich trained a deep neural network with photographs taken by cameras mounted on a hiker’s head. They could then fly a drone along forest paths. Now, along with researchers from a Madrid University, they have used city datasets to train the rules for navigating through streets without running into anything.

DroNet is a convolutional neural network, designed as a fast 8-layers residual network. It produces two outputs for each single input image: A steering angle to keep the drone navigating while avoiding obstacles, and a collision probability to let the drone recognize dangerous situations and promptly react to them.

The researchers publicly release all their datasets, code, and trained networks. Learn more at the DroNet project website, and the research page on deep learning. See also the video DroNet: Learning to Fly by Driving.

No parcel drones. No robo-trucks – Teamsters driver union delivers its demands to UPS

The Teamsters union and UPS are holding labor negotiations that cover 260,000 union workers in North America. Reportedly, one of the union demands is a prohibition on “driverless trucks, drones, robots, and other driverless technology.” In Teamsters Union Says ‘No’ to UPS Drones, we find this:

“With a smaller carbon footprint and ever-increasing sophisticated, AI-infused behavior, it makes sense to transition to individual aerial deliveries, not to mention the convenience on behalf of the customer. On the other hand, one completely understands and empathizes with the aversion truck drivers have toward this stark, autonomous future. If it feels like their jobs are being endangered by the incredible exponential growth in technology, it’s because they are. Hence, a series of discussions soon to be cemented into policy, with one side trying to slow things down in order to survive, and another eager to march into the fully autonomous future.”

Aurora Flight Sciences and Socionext Develop Radar-Enabled Collision Protection Solution for Drones

Aurora Flight Sciences is collaborating with Socionext Inc. on a Radar Flight Control Module that exists as a single-chip 24GHz radar. It includes range measurement software and the radar can detect multiple objects, objects in open spaces, and target distance and speed. The RFCM talks to the flight controller and provides...