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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Path Planning of UGV Based on Bézier Curves
TL;DR: A novel path planning method considering Bézier curves and a two-layer planning framework that is implemented on a modified Polaris RZR 800 UGV and demonstrates the viability of the proposed method.
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Vehicle Localization in Outdoor Mountainous Forested Paths and Extension of Two-Dimensional Road Centerline Maps to Three-Dimensional Maps
TL;DR: Experimental results in large-scale real mountainous woodland environments show the robustness and simplicity of the proposed approach for vehicle localization and 3-D map extension.
Proceedings ArticleDOI
Real-time adaptive non-holonomic motion planning in unforeseen dynamic environments
Sterling McLeod,Jing Xiao +1 more
TL;DR: An approach is introduced to smoothly switch trajectories by generating feasible non-holonomic trajectory segments on the fly as the robot moves in such an environment, extending the real-time adaptive motion planning (RAMP) approach that is used for holonomic motion.
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Real-Life Implementation of a GPS-Based Path-Following System for an Autonomous Vehicle.
Alexander de Winter,Simone Baldi +1 more
TL;DR: The tests show that the proposed path-following system is able to perform in real-time while satisfying comfort and trajectory tracking requirements: in particular, the tracking error was within 16 cm, which is compatible with the 13 cm precision of the Spatial Dual GPS.
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Low cost sensing for autonomous car driving in highways
TL;DR: This paper presents a viability study on autonomous car driving in highways using low cost sensors for on-the-spot decision-making in the self-driving car industry using low-cost sensors for highway safety.
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