Abstract
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.
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Ryoo, YJ. (2007). Neural Network Control for Visual Guidance System of Mobile Robot. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71629-7_77
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DOI: https://doi.org/10.1007/978-3-540-71629-7_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71590-0
Online ISBN: 978-3-540-71629-7
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