Autonomous Robotic Vehicle Road Following
IEEE Transactions on Pattern Analysis and Machine Intelligence
Intelligent control for autonomous systems
IEEE Spectrum
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
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
Stereo- and neural network-based pedestrian detection
IEEE Transactions on Intelligent Transportation Systems
Neural Network Control for Visual Guidance System of Mobile Robot
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
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This paper describes image technology using a neural network system for an automatic guided vehicle to follow a lane. Without complicated image processing from the image of a lane to the vehicle-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 system replaces the nonlinear relation of image information to a steering angle of vehicle on the real ground. For image information, the vanishing point and vanishing line of lane on a camera image are used. In a straight and curved lane, the driving performances by the proposed technology are measured in simulation and experimental test.