Appearance-Based Minimalistic Metric Slam

IEEE International Conference on Intelligent Robots and Systems

Volumn 1, Issue , 2003, Pages 194-199

  Rybski, Paul E ^a   Roumeliotis, Stergios I ^a   Gini, Maria ^a   Papanikolopoulos, Nikolaos ^a  

^a University of Minnesota   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; IMAGE PROCESSING; IMAGE RECORDING; IMAGE SENSORS; KALMAN FILTERING; MONTE CARLO METHODS;

EXTENDED KALMAN FILTERS (EKF); MONTE CARLO LOCALIZATION;

ROBOTICS;

EID: 0346149800     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. M. Betke and L. Gurvits. Mobile robot localization using landmarks. IEEE Transactions on Robotics and Automation, 13(2):251-263, April 1997.
2. F. Dellaert and A. Stroupe. Linear 2d localization and mapping for single and multiple robots. In Proc. of the IEEE Int'l Conf. on Robotics and Automation, May 2002.
3. M. W. M. G. Dissanayake, P. Newman, S. Clark, H. F. Durrant-Whyte, and M. Csorba. A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans. on Robotics and Automation, 17(3):229-241, June 2001.
4. T. Duckett, S. Marsland, and J. Shapiro. Learning globally consistent maps by relaxation. In Proc. of the IEEE Int'l Conf. on Robotics and Automation, volume 4, pages 3841-3846, 2000.
5. A. Gelb. Applied Optimal Estimation. MIT Press, 1994.
6. A. Howard, M. Matarić, and G. Sukhatme. Localization for mobile robot teams using maximum likelihood estimation. In Proc. of the IEEE/RSJ Int'l Conf. on Intelligent Robots and Systems, EPFL Switzerland, Sept. 2002.
7. KLT: An implementation of the Kanade-Lucas-Tomasi feature tracker, http://robotics.stanford.edu/̃birch/klt/.
8. B. 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.
9. J. J. Leonard and H. F. Durrant-Whyte. Mobile robot localization by tracking geometric beacons. IEEE Trans. on Robotics and Automation, 7(3):376-382, 1991.
10. D. Lowe. Object recognition from local scale-invariant features. In Proceedings of the Seventh IEEE International Conference on Computer Vision, pages 1150-7, 1999.
11. B.D. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. IJCAI, pages 674-679, 1981.
12. P. S. Maybeck. Stochastic Models, Estimation and Control, volume 141-142 of Mathematics in Science and Engineering. Academic Press, 1982.
13. J. Neira and J. Tardos. Data association in stochastic mapping using the joint compatibility test. IEEE Trans. on Robotics and Automation, 17(6):890-897, Dec. 2001.
14. S. I. Roumeliotis and G. A. Bekey. Bayesian estimation and kalman filtering: A unified framework for mobile robot localization. In Proc. of the IEEE Int'l Conf. on Robotics and Automation, pages 2985-2992, San Francisco, CA, April 2000.
15. P. E. Rybski, S. A. Stoeter, M. Gini, D. F. Hougen, and N. Papanikolopoulos. Performance of a distributed robotic system using shared communications channels. IEEE Trans. on Robotics and Automation, 22(5):713-727, Oct. 2002.
16. P. E. Rybski, F. Zacharias, J.-F. Lett. O. Masoud, M. Gini, and N. Papanikolopoulos. Using visual features to build topological maps of indoor environments. In Proc. of the IEEE Int'l Conf. on Robotics and Automation, 2003.
17. H. Shatkay and L. Kaelbling. Learning topological maps with weak local odometric information. In Proc. of the 15th Joint Conf. on Artificial Intelligence, pages 920-927, San Mateo, CA, 1997. Morgan Kaufmann.
18. R. Smith, M. Self, and P. Cheeseman. Estimating uncertain spatial relationships in robotics. In I. J. Cox and G. T. Wilfong, editors, Autonomous Robot Vehicles, pages 167-193. Springer-Verlag, 1990.
19. S. Thrun, W. Burgard, and D. Fox. A probabilistic approach to concurrent mapping and localization for mobile robots. Machine Learning, 31:29-53, 1998.
20. S. Thrun, D. Fox, W. Burgard, and F. Dellaert. Robust monte carlo localization for mobile robots. Artificial Intelligence, 101:99-141, 2000.
21. C. Tomasi and T. Kanade. Detection and tracking of point features. Technical report, School of Computer Science, Carnegie Mellon University, April 1991.
22. I. Ulrich and I. Nourbakhsh. Appearance-based place recognition for topological localization. In Proc. of the IEEE Int'l Conf. on Robotics and Automation, pages 1023-1029, San Francisco, CA, April 2000.