Intelligent control for autonomous systems
IEEE Spectrum
Neural Network Perception for Mobile Robot Guidance
Neural Network Perception for Mobile Robot Guidance
Vision and Navigation: The Carnegie Mellon Navlab
Vision and Navigation: The Carnegie Mellon Navlab
Image technology for camera-based automatic guided vehicle
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
Stereo- and neural network-based pedestrian detection
IEEE Transactions on Intelligent Transportation Systems
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This paper describes a neural network control for a visual guidance system of a mobile robot to follow a guideline. Without complicated geometric reasoning from the image of a guideline to the robot-centered representation of a bird's eye view in conventional studies, the proposed system transfers the input of image information into the output of a steering angle directly. The neural network controller replaces the nonlinear relation of image information to a steering angle of robot on the real ground. For image information, the feature points of guideline are extracted from a camera image. In a straight and curved guideline, the driving performances by the proposed technology are measured in simulation and experimental test.