Abstract
In this paper we present a navigation system based on decision trees and CBR (Case-Based reasoning) to guide an autonomous robot. The robot has only real-time visual feedback, and the image processing is performed by CNNs to take advantage of the parallel computation. We successfully tested the system on a SW simulator.
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Pazienza, G.E., Golobardes-Ribé, E., Vilasís-Cardona, X., Balsi, M. (2007). Decision Trees and CBR for the Navigation System of a CNN-based Autonomous Robot. In: Castillo, O., Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Hybrid Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37421-3_11
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DOI: https://doi.org/10.1007/978-3-540-37421-3_11
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