Ergen, Erkut Erhan.

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.