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Proceedings Paper

New vision system and navigation algorithm for an autonomous ground vehicle
Author(s): Hokchhay Tann; Bicky Shakya; Alex C. Merchen; Benjamin C. Williams; Abhishek Khanal; Jiajia Zhao; David J. Ahlgren
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Paper Abstract

Improvements were made to the intelligence algorithms of an autonomously operating ground vehicle, Q, which competed in the 2013 Intelligent Ground Vehicle Competition (IGVC). The IGVC required the vehicle to first navigate between two white lines on a grassy obstacle course, then pass through eight GPS waypoints, and pass through a final obstacle field. Modifications to Q included a new vision system with a more effective image processing algorithm for white line extraction. The path-planning algorithm adopted the vision system, creating smoother, more reliable navigation. With these improvements, Q successfully completed the basic autonomous navigation challenge, finishing tenth out of over 50 teams.

Paper Details

Date Published: 3 February 2014
PDF: 8 pages
Proc. SPIE 9025, Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques, 90250T (3 February 2014); doi: 10.1117/12.2045520
Show Author Affiliations
Hokchhay Tann, Trinity College (United States)
Bicky Shakya, Trinity College (United States)
Alex C. Merchen, Trinity College (United States)
Benjamin C. Williams, Trinity College (United States)
Abhishek Khanal, Trinity College (United States)
Jiajia Zhao, Trinity College (United States)
David J. Ahlgren, Trinity College (United States)

Published in SPIE Proceedings Vol. 9025:
Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques
Juha Röning; David Casasent, Editor(s)

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