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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Journal ArticleDOI
A dynamic colour perception system for autonomous robot navigation on unmarked roads
TL;DR: The results of this study show that fairly robust navigation strategies can be generated by a robot equipped with a dynamic active-vision based control system represented by an artificial neural network synthesized using evolutionary computation techniques.
Journal ArticleDOI
A Cross-domain Survey of Metrics for Modelling and Evaluating Collisions
TL;DR: This survey evaluates the state-of-the-art of collision metrics, and assesses which are likely to aid in the establishment and support of autonomous system collision modelling.
Dissertation
Trajectory planning and tracking for autonomous vehicles navigation
TL;DR: In this article, the authors propose an approach based on the methode recursive de Newton-Euler, which has been used extensively in the domain of robot control and navigation. But this methode is not suitable for the case of vehicules.
Proceedings ArticleDOI
High-Definition Map Combined Local Motion Planning and Obstacle Avoidance for Autonomous Driving
TL;DR: In this article, a local motion planning method combined with high-definition (HD) maps is presented to improve the safety and comfort of the obstacle avoidance process, and an inertia-like path selection algorithm based on this planning method is proposed.
Journal ArticleDOI
Communications and Driver Monitoring Aids for Fostering SAE Level-4 Road Vehicles Automation
Felipe Jiménez,Jose E. Naranjo,Sofía Sánchez,Francisco Serradilla,Elisa Pérez,Maria José Hernández,Trinidad Ruiz +6 more
TL;DR: This paper proposes the combination of cooperative systems with automated driving to offer a wider range of information to the vehicle than on-board sensors currently provide, which includes the actual deployment of a cooperative corridor on a highway.
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