Valgren, Christoffer and Duckett, Tom and Lilienthal , Achim (2007) Incremental spectral clustering and its application to topological mapping. In: Proceedings of ICRA2007, IEEE International Conference on Robotics and Automation, April 1014, 2007, Roma, Italy.
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Incremental_Spectral_Clustering__Paper.pdf 324Kb 
Abstract
This paper presents a novel use of spectral clustering algorithms to support cases where the entries in the affinity matrix are costly to compute. The method is incremental – the
spectral clustering algorithm is applied to the affinity matrix after each row/column is added – which makes it possible to inspect the clusters as new data points are added. The method is well suited to the problem of appearancebased, online topological mapping for mobile robots. In this problem domain, we show that we can reduce environmentdependent parameters of the clustering algorithm to just a single, intuitive parameter. Experimental results in large outdoor and indoor environments
show that we can close loops correctly by computing only a fraction of the entries in the affinity matrix. The accompanying video clip shows how an example map is produced by the
algorithm.
Item Type:  Conference or Workshop Item (Paper) 

Additional Information:  This paper presents a novel use of spectral clustering algorithms to support cases where the entries in the affinity matrix are costly to compute. The method is incremental – the spectral clustering algorithm is applied to the affinity matrix after each row/column is added – which makes it possible to inspect the clusters as new data points are added. The method is well suited to the problem of appearancebased, online topological mapping for mobile robots. In this problem domain, we show that we can reduce environmentdependent parameters of the clustering algorithm to just a single, intuitive parameter. Experimental results in large outdoor and indoor environments show that we can close loops correctly by computing only a fraction of the entries in the affinity matrix. The accompanying video clip shows how an example map is produced by the algorithm. 
Keywords:  mobile robot, topological mapping, SLAM, robot vision 
Subjects:  G Mathematical and Computer Sciences > G760 Machine Learning H Engineering > H671 Robotics G Mathematical and Computer Sciences > G740 Computer Vision 
Divisions:  College of Science > School of Computer Science 
ID Code:  1685 
Deposited By:  Tom Duckett 
Deposited On:  20 Nov 2008 16:32 
Last Modified:  13 Mar 2013 08:30 
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