Abstract
The application of the Kohonen self-organizing topology preserving neural network for learning and developing a minimal representation for the open environment for mobile robot navigation is presented in this paper. The input to the algorithm is the coordinates of randomly selected points in the open environment. No specific knowledge of the size, number, and shape of the obstacles is needed by the network. The parameter selection for the network is discussed and two illustrative examples are presented.
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© 1993 Springer Science+Business Media New York
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Najand, S., Lo, ZP., Bavarian, B. (1993). Application of Self-Organizing Neural Networks for Mobile Robot Environment Learning. In: Bekey, G.A., Goldberg, K.Y. (eds) Neural Networks in Robotics. The Springer International Series in Engineering and Computer Science, vol 202. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3180-7_5
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DOI: https://doi.org/10.1007/978-1-4615-3180-7_5
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