A Personal Account of the Development of Stanley, the Robot That Won the DARPA Grand Challenge
نویسنده
چکیده
Stanford on Stanley, the winning robot in the DARPA Grand Challenge. Between July 2004 and October 2005, my then-postdoc Michael Montemerlo and I led a team of students, engineers, and professionals with the single vision of claiming one of the most prestigious trophies in the field of robotics: the DARPA Grand Challenge (DARPA 2004).1 The Grand Challenge, organized by the U.S. government, was unprecedented in the nation’s history. It was the first time that the U.S. Congress had appropriated a cash price for advancing technological innovation. My team won this prize, competing with some 194 other teams. Stanley was the fastest of five robotic vehicles that, on October 8, 2005, successfully navigated a 131.6-mile-long course through California’s Mojave Desert. This essay is not about the technology behind our success; for that I refer the interested reader to recent articles on the technical aspects of Stanley (Dahlkamp et al. 2006; Montemerlo et al. 2006; Stavens and Thrun 2006; Thrun, Montemerlo, and Aron 2006; Thrun et al. 2006). Instead, this is my personal story of leading the Stanford Racing Team. It is the story of a team of people who built an autonomous robot in record time. It is also a success story for the field of artificial intelligence, as Stanley used some state of the art AI methods in areas such as probabilistic inference, machine learning, and computer vision. Of course, it is also the story of a step towards a technology that, one day, might fundamentally change our lives.
منابع مشابه
Winning the DARPA Grand Challenge with an AI Robot
This paper describes the software architecture of Stanley, an autonomous land vehicle developed for high-speed desert driving without human intervention. The vehicle recently won the DARPA Grand Challenge, a major robotics competition. The article describes the software architecture of the robot, which relied pervasively on state-of-the-art AI technologies, such as machine learning and probabil...
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This article describes the robot Stanley, which won the 2005 DARPA Grand Challenge. Stanley was developed for high-speed desert driving without manual intervention. The robot’s software system relied predominately on state-of-the-art arti cial intelligence technologies, such as machine learning and probabilistic reasoning. This article describes the major components of this architecture, and di...
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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 b...
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ورودعنوان ژورنال:
- AI Magazine
دوره 27 شماره
صفحات -
تاریخ انتشار 2006