Stanley: The Robot that Won the DARPA Grand Challenge
Sebastian Thrun,Michael Montemerlo,Hendrik Dahlkamp,David Stavens,Andrei Aron,James Diebel,Philip Fong,John Gale,Morgan Halpenny,Gabriel M. Hoffmann,Kenny Lau,Celia M. Oakley,Mark Palatucci,Vaughan R. Pratt,Pascal Stang,Sven Strohband,Cedric Dupont,Lars-Erik Jendrossek,Christian Koelen,Charles Markey,Carlo Rummel,Joe van Niekerk,Eric Jensen,Philippe Alessandrini,Gary Bradski,Bob Davies,Scott M. Ettinger,Adrian Kaehler,Ara V. Nefian,Pamela Mahoney +29 more
TLDR
The robot Stanley, which won the 2005 DARPA Grand Challenge, was developed for high‐speed desert driving without manual intervention and relied predominately on state‐of‐the‐art artificial intelligence technologies, such as machine learning and probabilistic reasoning.Abstract:
This article describes the robot Stanley, which won the 2005 DARPA Grand Challenge. Stanley was developed for high-speed desert driving without human intervention. The robot’s software system relied predominately on state-of-the-art AI technologies, such as machine learning and probabilistic reasoning. This article describes the major components of this architecture, and discusses the results of the Grand Challenge race.read more
Citations
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Looking Ahead: Anticipating Pedestrians Crossing with Future Frames Prediction
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References
More filters
Journal ArticleDOI
Pattern Classification and Scene Analysis.
Book
Pattern classification and scene analysis
Richard O. Duda,Peter E. Hart +1 more
TL;DR: In this article, a unified, comprehensive and up-to-date treatment of both statistical and descriptive methods for pattern recognition is provided, including Bayesian decision theory, supervised and unsupervised learning, nonparametric techniques, discriminant analysis, clustering, preprosessing of pictorial data, spatial filtering, shape description techniques, perspective transformations, projective invariants, linguistic procedures, and artificial intelligence techniques for scene analysis.
Proceedings ArticleDOI
New extension of the Kalman filter to nonlinear systems
Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: It is argued that the ease of implementation and more accurate estimation features of the new filter recommend its use over the EKF in virtually all applications.
Book
Fundamentals of Vehicle Dynamics
TL;DR: In this article, the authors attempt to find a middle ground by balancing engineering principles and equations of use to every automotive engineer with practical explanations of the mechanics involved, so that those without a formal engineering degree can still comprehend and use most of the principles discussed.
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