Abstract
In this paper we propose a method of fuzzy decision tree for solving pattern recognition and classification problems related to tactile sensing. A tactile sensing system is a robotic device which obtains the shape, hardness, surface details of contacting objects. Fuzzy decision trees play important roles in many fields such as pattern recognition and classification. We have tried to use tactile images for inputting the data. It provides a framework that generates fuzzy decision trees, as well as fuzzy sets for input data. The algorithm based fuzzy decision tree firstly collect enough training data for generating a practical decision tree. It then uses fuzzy statistics to calculate fuzzy sets for representing the training data in order to increase generation speed. The algorithm is applied to a general purpose tactile force sensing system. Based on the fuzzy decision tree, the contact objects can be online recognized precisely.
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© 2009 Springer-Verlag Berlin Heidelberg
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Bing, G. (2009). Pattern Recognition and Classification for Tactile Sensor Based on Fuzzy Decision Tree. In: Cao, By., Zhang, Cy., Li, Tf. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88914-4_58
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DOI: https://doi.org/10.1007/978-3-540-88914-4_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88913-7
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