This research work focuses on the design and implementation of the vision-guided autonomous vehicles that represented BYU in the 2005 (Team Urckbot) and 2006 (Y-Clops) Intelligent Ground Vehicle Competition (IGVC), in which autonomous vehicles navigate a course marked with white lines while avoiding obstacles consisting of orange construction barrels, white buckets and potholes. Our project began in the context of a senior capstone course in which multi-disciplinary teams of five students were responsible for the design, construction, and programming of their own robots. Each team received a computer motherboard, a camera, and a small budget for the purchase of additional hardware, including a chassis and motors. The resource constraints resulted in a simple vision-based design that processes the sequence of images from the single camera to determine motor controls. Color segmentation separates white and orange from each image, and then the segmented image is examined using a 10x10 grid system, effectively creating a low resolution picture for each of the two colors. Depending on its position, each filled grid square influences the selection of an appropriate turn magnitude. Motor commands determined from the white and orange images are then combined to yield the final motion command for video frame.

 Project Sponsors:

 Shafer Scholarship, Embedded System Center, and ECEn Dept.

 Collaborators:

 Students:

 Chris Archibald, Aaron Dennis, Spencer Fowers, Chris Greco, Kirt Lillywhite, Evan Millar, and Beau Tippetts

1. B.J. Tippetts, K.D. Lillywhite, S.G. Fowers, A.W. Dennis, C.R. Greco, D.J. Lee, and J.K. Archibald, “A Simple, Inexpensive, and Effective Implementation of a Vision Guided Autonomous Robot”, SPIE Optics East, Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision, vol. 6382-35, 63840P, Boston, MA, USA, October 1-4, 2006.

2. C. Archibald, E.S. Millar, J.D. Anderson, J.K. Archibald, and D.J. Lee, “A Simple Approach to a Vision-guided Unmanned Vehicle”, SPIE Optics East, Robotics Technologies and Architectures, Intelligent Robots and Computer Vision XVIII, vol. 6006, p. 210-220, Boston, MA, USA, October 23-26, 2005.