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
More filters
Book
Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future Prospects
TL;DR: The next generation of autonomous vehicles will provide major improvements in traffic flow, fuel efficiency, and vehicle safety, and the deployment of auto-rickshaws will be a major step forward.
Proceedings ArticleDOI
Hierarchical Reinforcement Learning Combined with Motion Primitives for Automated Overtaking
TL;DR: In this article, a hierarchical reinforcement learning (HRL) framework for automated overtaking is presented, where the high-level decision making and low-level control are combined by defining MPs with different time intervals.
Proceedings ArticleDOI
Robust extraction of shady roads for vision-based UGV navigation
TL;DR: A new vision-based approach where flexible number of models are built from sample data, which gives more robust results and, in particular, recognizes shadows on road as drivable road surface instead of non-road.
Proceedings ArticleDOI
Low speed automation: Technical feasibility of the driving sharing in urban areas
TL;DR: The technical feasibility of fully automated driving at speeds below 50 km/h in urban and suburban areas with an adequate infrastructure quality and no intersections, known road geometry and lane markings available is presented.
Proceedings ArticleDOI
Design and development of a benchmarking testbed for the Factory of the Future
Sven Schneider,Frederik Hegger,Nico Hochgeschwender,Rhama Dwiputra,Alexander Moriarty,Jakob Berghofer,Gerhard K. Kraetzschmar +6 more
TL;DR: The design and development of a benchmarking testbed for the Factory of the Future enables to study, compare and assess robotics scenarios involving the integration of mobile robots and manipulators with automation equipment, large-scale integration of service robots and industrial robots, cohabitation of robots and humans, and cooperation of multiple robots and/or humans.
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.
Related Papers (5)
Autonomous driving in urban environments: Boss and the Urban Challenge
Chris Urmson,Joshua Anhalt,Drew Bagnell,Christopher R. Baker,Robert Bittner,Michael Clark,John M. Dolan,D Duggins,Tugrul Galatali,Christopher Geyer,Michele Gittleman,Sam Harbaugh,Martial Hebert,Thomas M. Howard,Sascha Kolski,Alonzo Kelly,Maxim Likhachev,Matthew McNaughton,Nick Miller,Kevin Peterson,Brian Pilnick,Ragunathan Rajkumar,Paul E. Rybski,Bryan Salesky,Young-Woo Seo,Sanjiv Singh,Jarrod M. Snider,Anthony Stentz,William Whittaker,Ziv Wolkowicki,Jason Ziglar,Hong Bae,Thomas G. Brown,Daniel Demitrish,Bakhtiar Brian Litkouhi,Jim Nickolaou,Varsha Sadekar,Wende Zhang,Joshua Struble,Michael Taylor,Michael Darms,Dave Ferguson +41 more