Year: 2006
Type: article
Abstract: 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 artificial intelligence technologies, such as machine learning and probabilistic reasoning. This paper describes the major components of this architecture, and discusses the results of the Grand Challenge race. © 2006 Wiley Periodicals, Inc.
Source: Journal of Field Robotics
DOI: 10.1002/rob.20147
Authors: Sebastian Thrun, Mike Montemerlo, Hendrik Dahlkamp, David Stavens, Andrei Aron, James Diebel, Philip Fong, John Gale, Morgan Halpenny, Gabriel Hoffmann, Kenny Lau, Celia Oakley, Mark Palatucci, Vaughan 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 Ettinger, Adrian Kaehler, Ara Nefian, Pamela Mahoney
Institutions: Stanford University, Intel (United States)
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2154844948