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Proceedings Paper

Development of a vision system for an intelligent ground vehicle
Author(s): Robert L. Nagel; Kenneth Perry; Robert B. Stone; Daniel A. McAdams
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Paper Abstract

The development of a vision system for an autonomous ground vehicle designed and constructed for the Intelligent Ground Vehicle Competition (IGVC) is discussed. The requirements for the vision system of the autonomous vehicle are explored via functional analysis considering the flows (materials, energies and signals) into the vehicle and the changes required of each flow within the vehicle system. Functional analysis leads to a vision system based on a laser range finder (LIDAR) and a camera. Input from the vision system is processed via a ray-casting algorithm whereby the camera data and the LIDAR data are analyzed as a single array of points representing obstacle locations, which for the IGVC, consist of white lines on the horizontal plane and construction markers on the vertical plane. Functional analysis also leads to a multithreaded application where the ray-casting algorithm is a single thread of the vehicle's software, which consists of multiple threads controlling motion, providing feedback, and processing the data from the camera and LIDAR. LIDAR data is collected as distances and angles from the front of the vehicle to obstacles. Camera data is processed using an adaptive threshold algorithm to identify color changes within the collected image; the image is also corrected for camera angle distortion, adjusted to the global coordinate system, and processed using least-squares method to identify white boundary lines. Our IGVC robot, MAX, is utilized as the continuous example for all methods discussed in the paper. All testing and results provided are based on our IGVC robot, MAX, as well.

Paper Details

Date Published: 19 January 2009
PDF: 10 pages
Proc. SPIE 7252, Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques, 72520H (19 January 2009); doi: 10.1117/12.807769
Show Author Affiliations
Robert L. Nagel, Missouri Univ. of Science and Technology (United States)
Kenneth Perry, Missouri Univ. of Science and Technology (United States)
Robert B. Stone, Missouri Univ. of Science and Technology (United States)
Daniel A. McAdams, Texas A&M Univ. (United States)

Published in SPIE Proceedings Vol. 7252:
Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

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