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Unmanned systems: More independence for autonomous shuttles, Amazon improves delivery drones, UAS monitor oyster reefs

In this week’s roundup from the Association for Unmanned Vehicle Systems International, which highlights some of the latest news and headlines in unmanned vehicles and robotics, a new autonomous vehicle doesn't require a human supervisor on board, Amazon updates its delivery drone design, and mapping oyster reefs via drone.

EasyMile launches driverless shuttle capable of being remotely supervised EasyMile has announced the launch of its new EZ10 electric driverless shuttle, which is the first such vehicle in the world ready to operate without an on-board attendant, according to EasyMile.

The shuttle is supervised by a fully trained supervisor from a remote control center, who uses a real-time data stream to monitor the autonomous vehicle, and ensure communication with passengers.

“So we’re building a drone that isn’t just safe, but independently safe, using the latest artificial intelligence (AI) technologies.” Amazon says that some UAS are autonomous but not able to react to the unexpected, as they rely on communications systems for situational awareness.

The company says that if the flight environment of its drone changes, or the drone‘s mission commands it to come into contact with an object that wasn’t there previously—it will refuse to do so—it is independently safe.

For the UAS to descend for delivery, Amazon says that it needs a small area around the delivery location that is clear of people, animals, or obstacles, so it determines this by using explainable stereo vision in parallel with sophisticated AI algorithms trained to detect people and animals from above.

“Through the use of computer-vision techniques we’ve invented, our drones can recognize and avoid wires as they descend into, and ascend out of, a customer’s yard.” Amazon notes that it is also “thrilled” about the potential environmental impact that its UAS can have, as Prime Air is one of several sustainability initiatives to help achieve Shipment Zero, which is Amazon’s vision to make all Amazon shipments net zero carbon, with 50 percent of all shipments net zero by 2030.

“When it comes to emissions and energy efficiency, an electric drone, charged using sustainable means, traveling to drop off a package is a vast improvement over a car on the road,” Amazon says.

While most people go to the store now when they need an item, Amazon says that a service like Prime Air will allow consumers to order from home and stay home, which reduces emissions, and leads to significant savings on fuel usage.

Embry-Riddle, UCF partner to examine how UAS can be used to map oyster reefs With a focus on 21 oyster reefs near Edgewater, Florida, Embry-Riddle Aeronautical University and the University of Central Florida (UCF) have partnered to develop methodologies for remotely mapping regions that are difficult, and expensive, to monitor on site.

The 'Car Wrecks' Ahead in the World of Artificial Intelligence and Transportation

Fragile regulatory processes may prove as much cause for concern as fragile software systems when it comes to autonomous vehicle development, argued two Duke professors at a recent conference on the future of artificial intelligence.

Mary 'Missy' Cummings, professor in the Department of Electrical and Computer Engineering and director of the Humans and Autonomy Lab (HAL) at Duke, spoke about how the makers of autonomous vehicles are still unable to make the leap into full autonomy, remaining stuck in the automation stage.

A first look at Amazon’s new delivery drone

For the first time, Amazon today showed off its newest fully electric delivery drone at its first re:Mars conference in Las Vegas.

It’s an ingenious hexagonal hybrid design, though, that has very few moving parts and uses the shroud that protects its blades as its wings when it transitions from vertical, helicopter-like flight at takeoff to its airplane-like mode.

What’s maybe even more important, though, is that the drone is chock-full of sensors and a suite of compute modules that run a variety of machine learning models to keep the drone safe.

Today’s announcement marks the first time Amazon is publicly talking about those visual, thermal and ultrasonic sensors, which it designed in-house, and how the drone’s autonomous flight systems maneuver it to its landing spot.

When you see it fly in airplane mode, it looks a little bit like a TIE fighter, where the core holds all the sensors and navigation technology, as well as the package.

Besides the cool factor of the drone, though, which is probably a bit larger than you may expect, what Amazon is really emphasizing this week is the sensor suite and safety features it developed for the drone.

Ahead of today’s announcement, I sat down with Gur Kimchi, Amazon’s VP for its Prime Air program, to talk about the progress the company has made in recent years and what makes this new drone special.

that constantly monitor the drone’s flight envelope (which, thanks to its unique shape and controls, is far more flexible than that of a regular drone) and environment.

There are multiple sensors on all sides of the aircraft so that it can spot things that are far away, like an oncoming aircraft, as well as objects that are close, when the drone is landing, for example.

The drone also uses various machine learning models to, for example, detect other air traffic around it and react accordingly, or to detect people in the landing zone or to see a line over it (which is a really hard problem to solve, given that lines tend to be rather hard to detect).

The team also uses a technique known as Visual Simultaneous Localization and Mapping (VSLAM), which helps the drone build a map of its current environment, even when it doesn’t have any other previous information about a location or any GPS information.

What Kimchi stressed throughout our conversation is that Amazon’s approach goes beyond redundancy, which is a pretty obvious concept in aviation and involves having multiple instances of the same hardware on board.

But when it needs to find a place to land, its AI smarts kick in and the drone will try to find a safe place to land, away from people and objects —

Just the computational fluid dynamics simulations took up 30 million hours of AWS compute time (it’s good to own a large cloud when you want to build a novel, highly optimized drone, it seems).

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