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Advisor(s)
Abstract(s)
Ultrasonic, infrared, laser and other sensors are being applied
in robotics. Although combinations of these have allowed robots to navigate,
they are only suited for specific scenarios, depending on their limitations.
Recent advances in computer vision are turning cameras into useful
low-cost sensors that can operate in most types of environments. Cameras
enable robots to detect obstacles, recognize objects, obtain visual
odometry, detect and recognize people and gestures, among other possibilities.
In this paper we present a completely biologically inspired vision
system for robot navigation. It comprises stereo vision for obstacle detection,
and object recognition for landmark-based navigation. We employ
a novel keypoint descriptor which codes responses of cortical complex
cells. We also present a biologically inspired saliency component, based
on disparity and colour.