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
Computer Vision: Algorithms and Applications
TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Journal ArticleDOI
A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles
TL;DR: In this article, the authors present a survey of the state of the art on planning and control algorithms with particular regard to the urban environment, along with a discussion of their effectiveness.
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
TL;DR: This dissertation aims to provide a history of web exceptionalism from 1989 to 2002, a period chosen in order to explore its roots as well as specific cases up to and including the year in which descriptions of “Web 2.0” began to circulate.
Journal IssueDOI
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
TL;DR: Boss is an autonomous vehicle that uses on-board sensors to track other vehicles, detect static obstacles, and localize itself relative to a road model using a spiral system development process with a heavy emphasis on regular, regressive system testing.
Journal ArticleDOI
Predictive Active Steering Control for Autonomous Vehicle Systems
TL;DR: The effectiveness of the proposed MPC formulation is demonstrated by simulation and experimental tests up to 21 m/s on icy roads, and two approaches with different computational complexities are presented.
References
More filters
Book ChapterDOI
Knowledge-Based Training of Artificial Neural Networks for Autonomous Robot Driving
TL;DR: This chapter presents the neural network architecture and training techniques that allow ALVINN to drive in a variety of circumstances including single-lane paved and unpaved roads, multilane lined and unlined roads, and obstacle-ridden on-and off-road environments, at speeds of up to 55 miles per hour.
Proceedings Article
Winning the DARPA grand challenge with an AI robot
TL;DR: The article describes the software architecture of Stanley, an autonomous land vehicle developed for high-speed desert driving without human intervention which relied pervasively on state-of-the-art AI technologies, such as machine learning and probabilistic reasoning.
Proceedings ArticleDOI
Enhancing Supervised Terrain Classification with Predictive Unsupervised Learning
TL;DR: This paper describes a method for classifying the traversability of terrain by combining unsupervised learning of color models that predict scene geometry with supervised learning of the relationship between geometric features and traversability, and presents results from DARPA-conducted tests that demonstrate its effectiveness in a variety of outdoor environments.
Proceedings ArticleDOI
Interacting Markov Random Fields for Simultaneous Terrain Modeling and Obstacle Detection
TL;DR: A terrain model is introduced that includes spatial constraints on these quantities to exploit structure found in outdoor domains and use available sensor data more effectively and significantly improves ground height estimates and obstacle detection accuracy.
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