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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Receding horizon lateral vehicle control for pure pursuit path tracking
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The structural dynamics of macromolecular processes
Daniel Russel,Keren Lasker,Keren Lasker,Jeremy Phillips,Dina Schneidman-Duhovny,Javier A. Velázquez-Muriel,Andrej Sali +6 more
TL;DR: The relevant sources of information are reviewed and a framework for integrating the data to produce representations of dynamic processes of macromolecular complexes is introduced.
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Self-supervised learning to visually detect terrain surfaces for autonomous robots operating in forested terrain
Shengyan Zhou,Junqiang Xi,Matthew W. McDaniel,Takayuki Nishihata,Phil Salesses,Karl Iagnemma +5 more
TL;DR: A self-supervised sensing approach is introduced that attempts to robustly identify a drivable terrain surface for robots operating in forested terrain that employs both LIDAR and vision sensor data.
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Minimum curvature trajectory planning and control for an autonomous race car
Alexander Heilmeier,Alexander Wischnewski,Leonhard Hermansdorfer,Johannes Betz,Markus Lienkamp,Boris Lohmann +5 more
TL;DR: In this article, a software stack capable of planning a minimum curvature trajectory for an autonomous race car on the basis of an occupancy grid map is presented, and a controller design that allows the car to adapt to the occupancy grid maps.
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Motion segmentation and scene classification from 3D LIDAR data
TL;DR: A hierarchical data segmentation method from a 3D high-definition LIDAR laser scanner for cognitive scene analysis in context of outdoor vehicles and clusters the surrounding scene into point clouds representing static and dynamic objects which can attract the attention of the mission planning system.
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