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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Werner, F. Gretton, C. Maire, F. Sitte, J. |
| Copyright Year | 2008 |
| Description | Author affiliation: Fac. of Inf. Technol., Queensland Univ. of Technol., Brisbane, QLD (Werner, F.) |
| Abstract | In this paper we address the problem of topologically mapping environments which contain inherent perceptual aliasing caused by repeated environment structures. We propose an approach that does not use motion or odometric information but only a sequence of deterministic measurements observed by traversing an environment. Our algorithm implements a stochastic local search to build a small map which is consistent with local adjacency information extracted from a sequence of observations. Moreover, local adjacency information is incorporated to disambiguate places which are physically different but appear identical to the robots senses. Experiments show that the proposed method is capable of mapping environments with a high degree of perceptual aliasing, and that it infers a small map quickly. |
| Starting Page | 2890 |
| Ending Page | 2895 |
| File Size | 329623 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424420575 |
| DOI | 10.1109/IROS.2008.4650828 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-09-22 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | History Robot sensing systems Robots Merging Radiofrequency identification Navigation Data mining |
| Content Type | Text |
| Resource Type | Article |
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