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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Proceedings ArticleDOI
Towards an H-Mode for highly automated vehicles: driving with side sticks
TL;DR: In this article, the authors compare conventional interfaces (steering wheel and pedals) with different configurations of an active side stick and show that two dimensional interfaces have the potential to combine the driver-automation communication with acceptable drivability.
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Normal Distributions Transform Traversability Maps: LIDAR-Only Approach for Traversability Mapping in Outdoor Environments
TL;DR: A three-dimensional 3D traversability mapping algorithm for outdoor environments, able to classify sparsely vegetated areas as traversable, without compromising accuracy on other terrain types is proposed.
Proceedings ArticleDOI
Detecting obstacles and drop-offs using stereo and motion cues for safe local motion
TL;DR: A global color segmentation stereo method is proposed and its performance at detecting hazards against prior work using a local correlation stereo method and a novel drop-off detection scheme based on visual motion cues that adds to the performance of the stereo-vision methods is introduced.
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A Multimodal ADAS System for Unmarked Urban Scenarios Based on Road Context Understanding
TL;DR: A stereovision-based multimodal ADAS system designed for expanding the usability of ADAS functions, including lane-keeping assist, adaptive cruise control, and precrash system, to normal urban scenarios with unmarked roads is proposed.
Proceedings ArticleDOI
6-DOF localization for a mobile robot using outdoor 3D voxel maps
TL;DR: This paper describes outdoor localization for a mobile robot using a laser scanner and a three-dimensional voxel map that is based on outdoor point clouds that applies a particle filter to correct position errors in the laser measurement model for a 3D point cloud space.
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