Rise of the Drones
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Rise of the Drones
Investigating the future of unmanned aerial vehicles.
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Drone learns from humans how to navigate a forest - DIY Drones

Drone learns from humans how to navigate a forest - DIY Drones | Rise of the Drones | Scoop.it
From the ROS blog:
The Robotics Institute at CMU has been developing systems to learn from humans. Using a Machine Learning class of techniques called Imitation Learning the group has developed AI software for a small commercially available off-the-shelf ARdrone to autonomously fly through the dense trees for over 3.4 km in experimental runs. They are also developing methods to do longer range planning with such purely vision-guided UAVs. Such technology has a lot of potential impact for surveillance, search and rescue and allowing UAVs to safely share airspace with manned airspace.
ddrrnt's insight:

Watch the video at DIYdrones to see the drone fly through an unstructured environment. 


More re: Autopilot

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New miniature autopilot! Easypilot 3.0 | sUAS News

New miniature autopilot! Easypilot 3.0 | sUAS News | Rise of the Drones | Scoop.it

After a long period of development we are now proud to announce that our brand new NATO STANAG 4586 compliant autopilot, EasyPilot 3.0, is available for sale. Together with our field proven Ground Control Station software, SkyView GCS, it makes a perfect platform to get your unmanned vehicles flying, or improving performance of your current ones.


31 October 2012
By Gary Mortimer

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Drone that can dodge obstacles developed by US scientists

Drone that can dodge obstacles developed by US scientists | Rise of the Drones | Scoop.it

An unmanned drone that can fly around hazards such as trees and poles without human control has been developed, opening the possibility of more autonomous flight.


Now, however, researchers at New York's Cornell University have managed to develop software that will help drones to dodge obstacles.


In the experiments, a miniature helicopter equipped with a camera captures images as it flies. Software developed by assistant professor of computer science Ashutosh Saxena and his team turns the image in the drone's camera into a 3D model of its environment, and the robotic brain then uses an algorithm to determine which objects are obstacles.


In 53 flights in environments full of hazards, the robot managed to find a pathway without crashing into any obstacles - although the final two flights failed due to gusts of wind.


Eventually it is hoped that the drone will be able to calculate wind patterns and avoid moving objects such as birds.


The research is being funded by US Defence agency DARPA and drone-producer Lockheed Martin.


By Ben Bryant

08 Nov 2012

Telegraph.co.uk

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