Algorithms Allow MAVs to Avoid Obstacles with Single Camera and Neuromorphic Hardware

Clever programming enables new outdoor capabilities for micro air vehicles

2 min read
Algorithms Allow MAVs to Avoid Obstacles with Single Camera and Neuromorphic Hardware

Yesterday, we posted about some dirt cheap micro air vehicles on Kickstarter. Cheap hardware is great, but to make it do cool stuff, you usually need expensive (or at least, very clever) software. Researchers at Cornell have come up with a way to enable robotic aircraft to navigate around outdoor obstacles using just a single camera and hardware that mimics neuron architecture.

So, why is perceiving obstacles extremely important for aerial robots, and why are current methods based on stereo vision fundamentally limited? Here's what the researchers have to say:

Perceiving obstacles is extremely important for an aerial robot in order to avoid collisions. Methods based on stereo vision are fundamentally limited by the finite baseline between the stereo pairs, and fail in textureless regions and in presence of specular reflections. Active range-finding devices are either designed for indoor low-light environments (e.g., the Kinect), or are too heavy for aerial applications. More importantly, they demand more onboard power, which is at a premium for aerial vehicles.

Nicely put. This is especially relevant for small and cheap robots, because all you need is a single camera, minimal processing power, and even more minimal battery power. 

The new algorithm works by taking a single still frame from a camera stream and classifying the image into areas that are safe for the robot to pass through, and areas that aren't. To do this quickly and efficiently, the researchers are running their algorithm on a neuromorphic hardware platform based on the collective firing of a network of artificial neurons. Obstacles are separated out from backgrounds using a series of taught visual cues (like the fact that straight lines appear to converge at a distance, or the size of familiar objects), and he final platform will be able to process several frames per second using less than one watt of power. The system works quite well in practice: in 53 autonomous flights in obstacle-rich environments, the robot succeeded in reaching its objective without crashing into anything or killing anyone, with the final two flights being messed up by gusts of wind (they're working on compensating for that). Here's some video:

It works indoors on an AR Drone, too, as shown in some earlier research:

And here's some much earlier research doing 3D obstacle avoidance from monocular images on a robot car, which looks like fun:

So what's next?

Saxena plans to improve the robot's ability to respond to environment variations such as winds, and enable it to detect and avoid moving objects, like real birds; for testing purposes, he suggests having people throw tennis balls at the flying vehicle.

Heck yeah! SIGN ME UP!

"Low-Power Parallel Algorithms for Single Image based Obstacle Avoidance in Aerial Robots," by Ian Lenz, Mevlana Gemici, and Ashutosh Saxena from Cornell University, was presented last month at IROS 2012 in Portugal.

[ Cornell MAV ] via [ Cornell ]

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How Robots Can Help Us Act and Feel Younger

Toyota’s Gill Pratt on enhancing independence in old age

10 min read
An illustration of a woman making a salad with robotic arms around her holding vegetables and other salad ingredients.
Dan Page
Blue

By 2050, the global population aged 65 or more will be nearly double what it is today. The number of people over the age of 80 will triple, approaching half a billion. Supporting an aging population is a worldwide concern, but this demographic shift is especially pronounced in Japan, where more than a third of Japanese will be 65 or older by midcentury.

Toyota Research Institute (TRI), which was established by Toyota Motor Corp. in 2015 to explore autonomous cars, robotics, and “human amplification technologies,” has also been focusing a significant portion of its research on ways to help older people maintain their health, happiness, and independence as long as possible. While an important goal in itself, improving self-sufficiency for the elderly also reduces the amount of support they need from society more broadly. And without technological help, sustaining this population in an effective and dignified manner will grow increasingly difficult—first in Japan, but globally soon after.

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