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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aamodt, A., Plaza, E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications 7(1), 39–59 (1994)
Borenstein, J., Everett, H.R., Feng, L.: Navigating mobile robot: sensors and techniques. A.K. Peters, Ltd., Wellesley, MA (1996)
Chui, C.K.: An Introduction to Wavelets. Academic Press, London, England (1992)
Daubechies, I.: Orthonormal bases of compactly supported wavelets. Commun. Pure Appl. Math. 41(7), 909–996 (1988)
Fabrizi, E., Panzieri, S., Ulivi, G.: Extracting topological features of indoor environment from sonar-based fuzzy maps. In: Proc. of the 6th International Conference on Intelligent Autonomous Systems, Venice, Italy (2000)
Fabrizi, E., Saffiotti, A.: Extracting topology-based maps from gridmaps. In: Proc. of Int. Conf. on Robotics and Automation, San Francisco, CA (2000)
Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Mateo, CA (1993)
Kuipers, B., Byun, Y.T.: A robot exploration and mapping strategy based on a semantic hierarchy of spatial representation. Journal of Robotics and Autonomous Systems 8, 47–63 (1991)
Mallat, S.G.: A Theory for Multiresolution Signal Decomposition: the Wavelet Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 11(7), 674–693 (1989)
Oriolo, G., Vendittelli, M., Ulivi, G.: Real-Time Map Building and navigation for Autonomous Robots in Unknown Environments. IEEE Transactions on Systems, Men and Cybernetics - Part B: Cybernetics 28(3), 316–333 (1998)
Panzieri, S., Petroselli, D., Ulivi, G.: Topological localization on indoor sonar-based fuzzy maps. In: Intelligent Autonomous System, pp. 596–603. IOS Press, Amsterdam, NL (2000)
Panzieri, S., Pascucci, F., Petroselli, D.: Auton. Navigation ARCHitecture for Intelligent Control (2002), www.dia.uniroma3.it/autom/labrob/anarchic
Schank, R.: Dynamic Memory: A Theory of Learning in Computers and People. Cambridge University Press, New York (1982)
Thrun, S.: Learning Metric-Topological Maps for Indoor Mobile Robot Navigation. Artificial Intelligence 99(1), 21–71 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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
Download citation
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
eBook Packages: Computer ScienceComputer Science (R0)