Date of Award
Honors Thesis (Open Access)
Colby College. Computer Science Dept.
Randolph M. Jones
Joseph E. Atkins
Dale J. Skrien
Unlike with traditional, computationally expensive algorithms, with Fuzzy Logic (FL) one does not have to own a fast computer or very precise measuring instruments to get good results. At lower costs, FL provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy, or missing input information. This is a facet of AI that appears to resemble human intuition in an important way: the ability to make quick and urgent judgment calls, on the spot, without the need to be absolutely certain of the input. The benefit brought by a low-cost solution like FL to mankind is widespread, as not only researchers of high caliber but also everyone can benefit from it. In the pages to come, we will delve, as deeply as the diagrams and expositions will allow, into the implementation of a fuzzy system designed for the purpose of tracking and predicting the motion of light-colored objects on dark background. Before that, however, is a brief history and introduction to FL.
Fuzzy Logic, position tracking.
Recommended CitationRodjito, Patrick, "Position tracking and motion prediction using Fuzzy Logic" (2006). Honors Theses. Paper 520.
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