Abstract
In this paper, we advance a novel approach to the problem of autonomous robot navigation. The environment is a complex indoor scene with very little a priori knowledge, and the navigation task is expressed in terms of natural language directives referring to natural features of the environment itself. The system is able to analyze digital images obtained by applying a sensor fusion algorithm to ultrasonic sensor readings. Such images are classified in different categories using a case-based approach. The architecture we propose relies on fuzzy theory for the construction of digital images, and wavelet functions for their representation and analysis.
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© 2007 Springer-Verlag Berlin Heidelberg
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Micarelli, A., Panzieri, S., Sansonetti, G. (2007). Case-Based Reasoning in Robot Indoor Navigation. In: Weber, R.O., Richter, M.M. (eds) Case-Based Reasoning Research and Development. ICCBR 2007. Lecture Notes in Computer Science(), vol 4626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74141-1_20
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DOI: https://doi.org/10.1007/978-3-540-74141-1_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74138-1
Online ISBN: 978-3-540-74141-1
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