Auxiliary Particle Filter Robot Localization from High-Dimensional Sensor Observations

@inproceedings{Vlassis2002AuxiliaryPF,
  title={Auxiliary Particle Filter Robot Localization from High-Dimensional Sensor Observations},
  author={Nikos A. Vlassis and Bas Terwijn and Ben J. A. Kr{\"o}se},
  booktitle={ICRA},
  year={2002}
}
We apply the auxiliary particle filter algorithm of Pitt and Shephard (1999) to the problem of robot localization. To deal with the high-dimensional sensor observations (images) and an unknown observation model, we propose the use of an inverted nonparametric observation model computed by nearest neighbor conditional density estimation. We show that the proposed model can lead to a fully adapted optimal filter, and is able to successfully handle image occlusion and robot kidnap. The proposed… CONTINUE READING
Highly Cited
This paper has 112 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 70 extracted citations

Choice mechanism of proposal distribution in particle filter

2010 8th World Congress on Intelligent Control and Automation • 2010
View 10 Excerpts
Highly Influenced

A novel mobile robot localization approach based on a model switching feature extraction

2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA) • 2012
View 1 Excerpt

113 Citations

051015'02'05'09'13'17
Citations per Year
Semantic Scholar estimates that this publication has 113 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 12 references

Novel - approach to nonlinear non - Gaussian Bayesian state estimation

A. Blake
IEE Proceedings - F Radar and signal processing • 1993

Consistent nonparametric regression ( with discussion )

D. J. Salmond, A. F. M. Smith
Ann . Statist . • 1977

Adaptive Control Pro esses: a Guided Tour

R. Bellman
Prin eton University Press, • 1961

Similar Papers

Loading similar papers…