Object Recognition Through Image Understanding for an Autonomous Mobile Robot
NAVAL POSTGRADUATE SCHOOL MONTEREY CA
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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 Yamabicos 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. Mobile robotics, Computer vision, Edge extraction, Obstacle avoidance.