Learning in Reality: A case study of Stanley, the robot that Won the DARPA Challenge
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چکیده
The Grand Challenge by the Defense Advances Research Projects Agency (DARPA) got a great impact on Machine Learning and Computer Vision research. Stanley was the first robot which firstly was able to drive autonomously a 175 mile course in desert terrain which was a great success in autonomous driving which may be leading to autonomous cares in urban environment in the future. Stanley faced a bunch of problems which needed to be solved to drive autonomously through the course. Some of those Problems are the terrain which has obstacles which need to be avoided and another is the driving speed which has to be maintained to win the challenge. Stanley uses therefore GPS, laser range scanners and a color camera to classify the road into drivable and non-drivable area. This classification is used to control speed and steering of the robot.
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تاریخ انتشار 2012