Christoffer Valgren, Tom Duckett and Achim J. Lilienthal
Incremental Spectral Clustering and Its Application to Topological Mapping
Proc. of IEEE Int. Conf. on Robotics and Automation (ICRA), 2007, pp. 4283-4288
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 appearance-based, on-line topological mapping for mobile robots. In this problem domain, we show that we can reduce environment-dependent 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.
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Bibtex:
@INPROCEEDINGS{Valgren_etal:ICRA:2007,
  author = {C. Valgren and T. Duckett and A. J. Lilienthal},
  title = {Incremental Spectral Clustering and Its Application to Topological Mapping},
  booktitle = {Proc. IEEE Int. Conf. on Robotics and Automation},
  year = {2007},
  pages = {4283--4288}
}