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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Optimizing Driverless Vehicles at Intersections
Ismail Zohdy,Hesham A. Rakha +1 more
TL;DR: The paper develops a heuristic optimization algorithm for driverless vehicles at unsignalized intersections using a multi-agent system and shows that the proposed system reduces the total delay by 35 seconds on average compared to traditional AWSC.
Journal ArticleDOI
Refining the execution of abstract actions with learned action models
Freek Stulp,Michael Beetz +1 more
TL;DR: A novel robot action execution system that learns success and performance models for possible specializations of abstract actions at execution time and can so use abstract actions for efficient reasoning, without compromising the performance of action execution.
Journal ArticleDOI
Exploring the landscapes of “computing: Digital, neuromorphic, unconventional - and beyond
TL;DR: This paper stake out the grounds of how a general concept of "computing" can be developed which comprises digital, neuromorphic, unconventional and possible future "com computing" paradigms, and locate anchor points for a foundational formal theory of a future computing-engineering discipline that includes, but will reach beyond, digital and neuromorphic computing.
Efficiently Using Cost Maps For Planning Complex Maneuvers
Dave Ferguson,Maxim Likhachev +1 more
TL;DR: This paper explains the design and use of grid-based cost maps that were used throughout the planning process and describes an algorithm for generating complex dynamically-feasible maneuvers for autonomous vehicles traveling at high speeds over large distances.
Journal ArticleDOI
CICP: Cluster Iterative Closest Point for Sparse-Dense Point Cloud Registration
TL;DR: A novel approach that surpasses the notion of density is proposed, which consists in matching points representing each local surface of source cloud with the points representing the corresponding local surfaces in the target cloud.
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