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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A new framework for mobile robot trajectory tracking using depth data and learning algorithms
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An Anytime Algorithm for Chance Constrained Stochastic Shortest Path Problems and Its Application to Aircraft Routing
TL;DR: In this paper, the authors formulated the aircraft routing problem under a dynamic and uncertain environment as a chance constrained stochastic shortest path (CC-SSP) problem and proposed an anytime algorithm for the problem.
Kognitive und kooperative Systeme in der Fahrzeugführung: Selektiver Rückblick über die letzten Dekaden und Spekulation über die Zukunft
TL;DR: This paper focuses on the domain of (air and ground) vehicle guidance and control and presents selected milestones in this field, beginning with autonomous vehicles and cognitive pilot support systems and synthesising it to a cooperative guidance and Control of cognitive systems, technically realised by a cognitive core and future standardized cognitive architectures.
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Localization based on multiple visual-metric maps
TL;DR: A fusion of monocular camera-based metric localization, IMU and odometry in dynamic environments of public roads is presented and shows that sensor fusion method offers lower average errors than GNSS and better coverage than vision-only one.
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Terrain Estimation for Planetary Exploration Robots
TL;DR: This paper presents a general approach to endow a robot with the ability to sense the terrain being traversed that relies on the estimation of motion states and physical variables pertaining to the interaction of the vehicle with the environment.
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