Object recognition through image understanding for an autonomous mobile robot
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Authors
DeClue, Mark Joseph.
Subjects
Mobile robotics
Computer vision
Edge extraction
Obstacle avoidance
Computer vision
Edge extraction
Obstacle avoidance
Advisors
Kanayama, Yutaka
Date of Issue
1993-09
Date
September 1993
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
The problem addressed in this research was to provide a capability for sensing previously unknown rectilinear, polyhedral-shaped objects in the operating environment of the autonomous mobile robot Yamabico-11. The approach to the system design was based on the application of edge extraction and least squares line fitting algorithms of PET92 to real-time camera images with subsequent filtering based on the environmental model of STE92. The output of this processing was employed in the recognition of obstacles and the determination of object range and dimensions. These measurements were then used in path tracking commands, supported by Yamabico's Model-based Mobile Robot Language (MML), for performing smooth, safe obstacle avoidance maneuvers. This work resulted in a system able to localize objects in images taken from the robot, provide location and size data, and cause proper path adjustments. Accuracies on the order of one to ten centimeters in range and one-half to two centimeters in dimensions were achieved.
Type
Thesis
Description
Series/Report No
Department
Computer Science
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
191 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.