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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Team AnnieWAY's autonomous system
Christoph Stiller,Sören Kammel,Benjamin Pitzer,Julius Ziegler,Moritz Werling,Tobias Gindele,Daniel Jagszent +6 more
TL;DR: AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that has successfully entered the finals of the DARPA Urban Challenge 2007 competition, is reported on.
Proceedings ArticleDOI
Accurate Mapping and Planning for Autonomous Racing
Leiv Andresen,Adrian Brandemuehl,Alex Hönger,Benson Kuan,Niclas Vödisch,Hermann Blum,Victor Reijgwart,Lukas Bernreiter,Lukas Schaupp,Jen Jen Chung,Mathias Bürki,Martin R. Oswald,Roland Siegwart,Abel Gawel +13 more
TL;DR: The presented solution combines early fusion of camera and LiDAR data, a layered mapping approach, and a planning approach that uses Bayesian filtering to achieve high-speed driving on unknown race tracks while creating accurate maps.
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Action Detection from a Robot-Car Perspective.
TL;DR: The new Road Event and Activity Detection dataset is presented, designed and created from an autonomous vehicle perspective to take action detection challenges to autonomous driving.
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System interdependence analysis for autonomous robots
TL;DR: A method of system interdependence analysis is presented to learn and quantitatively evaluate the coherence between performance indicators of different system components, as well as the influence of environmental parameters on the system.
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Survey on Cooperative Perception in an Automotive Context
TL;DR: In this paper , the authors provide an overview of the architectures available to create such a system as well as the challenges introduced by the cooperation, and also provide a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis of the cooperative perception.
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