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Cited by 308

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The SPmap: a probabilistic framework for simultaneous localization and map building

Castellanos, J.A., Montiel, J.M.M., Neira, J., Tardos, J.D.·1999·IEEE Transactions on Robotics and Automation
DOI 10.1109/70.795798
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Abstract

This article describes a rigorous and complete framework for the simultaneous localization and map building problem for mobile robots: the symmetries and perturbation map (SPmap), which is based on a general probabilistic representation of uncertain geometric information. We present a complete experiment with a LabMate/sup TM/ mobile robot navigating in a human-made indoor environment and equipped with a rotating 2D laser rangefinder. Experiments validate the appropriateness of our approach and provide a real measurement of the precision of the algorithms.

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Metadata

Authors
Castellanos, J. A., Montiel, J. M. M., Neira, J., & Tardos, J. D.
Venue
IEEE Transactions on Robotics and Automation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1999
Volume
15
Issue
5
Pages
948-952
ISSN
1042-296X (ISSN-L)
DOI
10.1109/70.795798
OpenAlex
W2148916113
Cited by
308
References
0
FWCI
26.94
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The SPmap: a probabilistic framework for simultaneous localization and map building. https://app.cochat.ai/papers/10.1109/70.795798
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Castellanos, J. A., Montiel, J. M. M., Neira, J., & Tardos, J. D. (1999). The SPmap: a probabilistic framework for simultaneous localization and map building. IEEE Transactions on Robotics and Automation. https://doi.org/10.1109/70.795798

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.