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September 1, 2006Journal of Field Robotics2,152 citationsOpen Access

Stanley: The robot that won the DARPA Grand Challenge

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STSebastian ThrunMMMike MontemerloHDHendrik Dahlkamp

Key Points

  • Detail the robotic architecture and software design of Stanley, an autonomous ground vehicle developed to complete high-speed desert driving without human intervention.
  • Designed an integrated system architecture powered by artificial intelligence, machine learning, and probabilistic reasoning algorithms.
  • Implemented real-time sensor fusion, environmental modeling, and adaptive path planning for off-road navigation.
  • Completed the off-road desert course autonomously to secure victory in the 2005 DARPA Grand Challenge.
  • Validated the effectiveness of probabilistic AI and learning algorithms for real-time high-speed navigation in unstructured, unpredictable terrains.

Abstract

Abstract This article describes the robot Stanley, which won the 2005 DARPA Grand Challenge. Stanley was developed for high‐speed desert driving without manual intervention. The robot's software system relied predominately on state‐of‐the‐art artificial intelligence technologies, such as machine learning and probabilistic reasoning. This paper describes the major components of this architecture, and discusses the results of the Grand Challenge race. © 2006 Wiley Periodicals, Inc.

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Cite This Study

Thrun et al. (2006) studied this question.

synapsesocial.com/papers/69fca4af8dc9aff719fa4816https://doi.org/10.1002/rob.20147
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