A rao-blackwellized particle filter for topological mapping

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2006, Issue , 2006, Pages 810-817

  Ranganathan, Ananth ^a   Dellaert, Frank ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN INFERENCE FRAMEWORK; PARTICLE FILTERING ALGORITHM; POST-PROCESSING; RAO-BLACKWELLIZED PARTICLE FILTER (RBPF);

INFERENCE ENGINES; MAPPING; ROBUSTNESS (CONTROL SYSTEMS); TOPOLOGY;

ALGORITHMS;

EID: 33845666266     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2006.1641809     Document Type: Conference Paper

References (29)

1. D. Blackwell and J.B. MacQueen. Ferguson distributions via polya urn schemes. Annals of Statistics, 1:353-355, 1973.
2. G. Casella and C.P. Robert. Rao-Blackwellisation of sampling schemes. Biometrika, 83(1):81-94, March 1996.
3. Y. Chen and G. Medioni. Object modelling by registration of multiple range images. In IEEE Intl. Conf. on Robotics and Automation (ICRA), pages 2724-2729, 1991.
4. H. Choset and K. Nagatani. Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization. IEEE Trans. Robot. Automat., 17(2):125-137, April 2001.
5. A. Doucet, S.Godsill, and C. Andrieu. On sequential monte carlo sampling methods for Bayesian filtering. Statistics and Computing, 10(3):197-208, 2000.
6. G. Dudek and D. Jugessur. Robust place recognition using local appearance based methods. In IEEE Intl. Conf. on Robotics and Automation (ICRA), pages 1030-1035, 2000.
7. T. S. Ferguson. A Bayesian analysis of some nonparametric problems. Annals of Statistics, 1:209-230, 1973.
8. R. Gutierrez-Osuna and R. C. Luo. Lola: Probabilistic navigation for topological maps. AI Magazine, 17(1):55-62, 1996.
9. J.-S. Gutmann and K. Konolige. Incremental mapping of large cyclic environments. In Proc. of the IEEE Intl. Symp. on Computational Intelligence in Robotics and Automation (CIRA), pages 318-325, November 2000.
10. D. Haehnel, W. Burgard, D. Fox, and S. Thrun. A highly efficient FastSLAM algorithm for generating cyclic maps of large-scale environments from raw laser range measurements. In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2003.
11. K. Kouzoubov and D. Austin. Hybrid topological/metric approach to SLAM. In IEEE Intl. Conf. on Robotics and Automation (ICRA), pages 872-877, 2004.
12. Benjamin Kuipers and Patrick Beeson. Bootstrap learning for place recognition. In AAAI Nat. Conf on Artificial Intelligence, pages 174-180, 2002.
13. B.J. Kuipers and Y.-T. Byun. A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations. Journal of Robotics and Autonomous Systems, 8:47-63, 1991.
14. F. Lu and E. Milios. Globally consistent range scan alignment for environment mapping. Autonomous Robots, pages 333-349, April 1997.
15. Stephen Marsland, Ulrich Nehmzow, and Tom Duckett. Learning to select distinctive landmarks for mobile robot navigation. Robotics and Autonomous Systems, 37(4):241-260, 2001.
16. J. Modayil, P. Beeson, and B. Kuipers. Using the topological skeleton for scalable global metrical map-building. In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2004.
17. M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit. FastSLAM: A factored solution to the simultaneous localization and mapping problem. In AAAI Nat. Conf. on Artificial Intelligence, 2002.
18. H.P. Moravec. Sensor fusion in certainty grids for mobile robots. AI Magazine, 9:61-74, 1988.
19. K. Murphy and S. Russell. Rao-Blackwellised particle filtering for dynamic Bayesian networks. In A. Doucet, N. de Freitas, and N. Gordon, editors, Sequential Monte Carlo Methods in Practice. Springer-Verlag, New York, January 2001.
20. A. Nijenhuis and H. Wilf. Combinatorial Algorithms. Academic Press, 2 edition, 1978.
21. A. Ranganathan and F. Dellaert. Inference in the space of topological maps: An MCMC-based approach. In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2004.
22. A. Ranganathan and F. Dellaert. Data driven MCMC for appearance-based topological mapping. In Robotics: Science and Systems I, 2005.
23. E. Remolina and B. Kuipers. Towards a general theory of topological maps. Artificial Intelligence, 152(1):47-104, 2004.
24. F. Savelli and B. Kuipers. Loop-closing and planarity in topological map-building. In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2004.
25. H. Shatkay and L. Kaelbling. Learning topological maps with weak local odometric information. In Proceedings of IJCAI-97, pages 920-929, 1997.
26. K. Sugihara. Some location problems for robot navigation using a single camera. CVGIP:Image Understanding, 42(1):112-129, April 1988.
27. S. Thrun, S. Gutmann, D. Fox, W. Burgard, and B. Kuipers. Integrating topological and metric maps for mobile robot navigation: A statistical approach. In AAAI, pages 989-995, 1998.
28. N. Tomatis, I. Nourbakhsh, and R. Siegwart. Simultaneous localization and map-building: a global topological model with local metric maps. In IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS), 2001.
29. N. Tomatis, I. Nourbakhsh, and R. Siegwart. Hybrid simultaneous localization and map building: Closing the loop with multi-hypotheses tracking. In IEEE Intl. Conf. on Robotics and Automation (ICRA), pages 2749-2754, 2002.