Author Type

Graduate Student

Date of Award

1997

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Raviv, Daniel

Abstract

This research explores the existing active-vision-based algorithms employed in today's autonomous navigation systems. Some of the popular range finding algorithms are introduced and presented with examples. In light of the existing methods, an active-vision-based method, which extracts visual cues from a sequence of 2D images, is proposed for autonomous navigation. The proposed algorithm merges the method titled 'Visual Threat Cues (VTCs) for Autonomous Navigation' developed by Kundur (1), with the structured-light-based methods. By combining these methods, a more practical and a simpler method for indoors autonomous navigation tasks is developed. A textured-pattern, which is projected onto the object surface by a slide projector, is used as the structured-light source, and the proposed approach is independent of the textured-pattern used. Several experiments are performed with the autonomous robot LOOMY to test the proposed algorithm, and the results are very promising.

Extent

103 p.

Comments

College of Engineering and Computer Science|FAU Electronic Theses and Dissertations Collection|Thesis (M.S.)--Florida Atlantic University, 1997.|College of Engineering and Computer Science

Identifier

FADT15425

Format

pdf

Download

Share

COinS