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Daphne Koller Publications

Fastslam: An efficient solution to the simultaneous localization and mapping problem with unknown data association (2004)

by S. Thrun, M. Montemerlo, D. Koller, B. Wegbreit, J. Nieto, and E. Nebot


Abstract: This article provides a comprehensive description of FastSLAM, a new family of algorithms for the simultaneous localization and mapping problem, which specifically address hard data association problems. The algorithm uses a particle filter for sampling robot paths, and extended Kalman filters for representing maps acquired by the vehicle. This article presents two variants of this algorithm, the original algorithm along with a more recent variant that provides improved performance in certain operating regimes. In addition to a mathematical derivation of the new algorithm, we present a proof of convergence and experimental results on its performance on real-world data.

Download Information

S. Thrun, M. Montemerlo, D. Koller, B. Wegbreit, J. Nieto, and E. Nebot (2004). "Fastslam: An efficient solution to the simultaneous localization and mapping problem with unknown data association." Journal of Machine Learning Research. To appear. pdf

Bibtex citation

@article{Thrun+al:04b,
  author = {S. Thrun and M. Montemerlo and D. Koller and B. Wegbreit and J. Nieto and E. Nebot},
  title = {Fastslam: {A}n efficient solution to the simultaneous localization and mapping problem 
        with unknown data association},
  journal = {Journal of Machine Learning Research},
  note = {To appear},
  year = 2004,
}

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