State-based SHOSLIF for indoor visual navigation

IEEE Transactions on Neural Networks

Volumn 11, Issue 6, 2000, Pages 1300-1314

  Chen, Shaoyun ^a,b   Weng, Juyang ^a,c  

^a IEEE   (United States)

^b KLA TENCOR CORPORATION   (United States)

^c Michigan State University   (United States)

Author keywords

Content based retrieval; Eigen subspace method; Incremental learning; Nearest neighbor regression; Observation driven Markov model (ODMM); Vision based navigation

Indexed keywords

EID: 0042001236     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.883430     Document Type: Article

References (39)

1. N. Ayache and O. D. Faugeras, "Maintaining representations of the environment of a mobile robot," IEEE Trans. Robot. Automat., vol. 5, no. 6, pp. 804-819, 1989.
2. L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone, Classification and Regression Trees. New York: Chapman & Hall, 1993.
3. S. Chen, C. F. N. Cowan, and P. M. Grant, "Orthogonal least squares learning algorithms for radial basis function networks," IEEE Trans. Neural Networks, vol. 2, pp. 302-309, Mar. 1991.
4. S. Chen and J. Weng, "SHOSLIF-N: SHOSLIF for autonomous navigation (Phase I)," Michigan State Univ., East Lansing, Tech. Rep. CPS-94-62.
5. T. M. Cover, "Estimation by the nearest neighbor rule," IEEE Trans. Inform. Theory, vol. IT-14, no. 1, pp. 50-55, January 1968.
6. D. R. Cox, "Statistical analysis of time series: Some recent developments," Scand. J. Statist., vol. 8, no. 2, pp. 93-115, 1981.
7. E. D. Dickmanns, "Machine perception exploiting high-level spatio-temporal models," in AGARD Lecture Series 185 'Machine Perception', Sept./Oct. 1992.
8. E. D. Dickmanns, "Vehicles capable of dynamic vision," in Proc. 15th Int. Joint Conf. Artificial Intell. (IJCAI-97), Nagoya, Japan, August 23-29, 1997.
9. I. E. Frank and J. H. Friedman, "A statistical review of some chemometrics regression tools," Technometrics, vol. 35, no. 2, pp. 109-148, 1993.
10. J. H. Friedman, "Multivariate adaptive regression splines (with discussion)," Ann. Statist., vol. 19, no. 1, pp. 1-141, 1991.
11. J. Hancock and C. E. Thorpe, "ELVIS: Eigenvectors for land vehicle image system,", CMU-RI-TR-94-43, Dec. 1994.
12. P. J. Huber, "Projection pursuit," Ann. Statist., vol. 13, no. 2, pp. 435-475, 1985.
13. X. D. Huang, Y. Ariki, and M. A. Jack, Hidden Markov Models for Speech Recognition. Edinburgh, U.K.: Edinburgh Univ. Press, 1990.
14. T. M. Jochem, "Vision-based tactical driving," The Robotics Institute, Carnegie-Mellon University, Tech. Rep. CMU-RI-TR-96-1 4, January 1996.
15. M. Kirby and L. Sirovich, "Application of the Karhunen-Loeve procedure for the characterization of human faces," IEEE Trans. Pattern Anal. Machine Intell., vol. 12, pp. 103-108, 1990.
16. K. Kluge and C. Thorpe, "Explicit models for robot road following," in Vision and Navigation: The Carnegie Mellon Navlab, C. Thorpe, Ed. Norwell, MA: Kluwer, 1990, pp. 25-38.
17. S. Koenig and R. G. Simmons, "A robot navigation architecture based on partially observable Markov decision process models," in Artificial Intelligence Based Mobile Robotics: Case Studies of Successful Robot Systems, D. Kortenkamp, R. P. Bonasso, and R. Murphy, Eds. Cambridge, MA: MIT Press, 1997.
18. X. Lebesgue and J. K. Argarwal, "Significant line segments for an indoor mobile robot," IEEE Trans. Robot. Automat., vol. 9, pp. 801-816, 1993.
19. M. Meng and A. C. Kak, "Mobile robot navigation using neural networks and nonmetrical environment models," IEEE Contr. Syst. Mag., pp. 31-42, Aug. 1993.
20. S. K. Murthy, "Automatic construction of decision trees from data: A multidisciplinary survey," Data Mining Knowledge Discovery, 1998, submitted for publication.
21. E. Oja and J. Karhunen, "On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix," J. Math. Anal. Applicat., vol. 106, pp. 69-84, 1985.
22. E. Oja, "Principal components, minor components, and linear neural networks," Neural Networks, vol. 5, pp. 927-936, 1992.
23. J. R. Quinlan, C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufmann, 1993.
24. D. A. Pomerleau, Neural Network Perception for Mobile Robot Guidance. Norwell, MA: Kluwer, 1993.
25. D. A. Pomerleau, "RALPH: Rapidly adapting lateral position handler," in Proc. IEEE Symp. Intell. Vehicles, Detroit, Michigan, Sept. 25-26, 1995.
26. L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. IEEE, vol. 77, no. 2, pp. 257-286, 1989.
27. M. Rosenblum and L. S. Davis, "An improved radial basis function network for visual autonomous road following," IEEE Trans. Neural Networks, vol. 7, pp. 1111-1120, Sept. 1996.
28. I. K. Sethi, "Decision tree performance enhancement using an artificial neural network implementation," in Artificial Neural Networks and Statistical Pattern Cognition, I. K. Sethi and A. K. Jain, Eds. Amsterdam, The Netherlands: North-Holland, 1991, pp. 71-88.
29. R. Simmons and S. Koenig, "Probabilistic robot navigation in partially observable environments," in Proc. 14th Int. Joint Conf. Artificial Intell. (IJCAI), 1995, pp. 1080-1087.
30. D. L. Swets and J. Weng, "Using discriminant eigenfeatures for image retrieval," IEEE Trans. Pattern Anal. Machine Intell., vol. 18, pp. 831-836, Aug. 1996.
31. C. Thorpe, Ed., Vision and Navigation: The Carnegie Mellon Navlab. Norwell, MA: Kluwer, 1990, pp. 9-23.
32. C. Thorpe, M. Herbert, T. Kanade, and S. Shafer, "Toward autonomous driving: The CMU Navlab," IEEE Expert, pp. 31-42, Aug. 1991.
33. M. Turk and A. Pentland, "Eigenfaces for recognition," J. Cognitive Neurosci., vol. 3, no. 1, pp. 71-86, 1991.
34. A. R. Webb and D. Lowe, "The optimized internal representation of multilayer classifier networks performs nonlinear discriminant analysis," Neural Networks, vol. 3, pp. 367-375, 1990.
35. J. Weng and S. Chen, "Incremental learning for vision-based navigation," in Proc. Int. Conf. Pattern Recognition, vol. IV, Vienna, Austria, August 1996, pp. 45-49.
36. J. Weng and S. Chen, "Vision-guided navigation using SHOSLIF," Neural Networks, vol. 11, pp. 1511-1529, 1998.
37. S. Yakowitz, "Nearest neighbor methods for time series analysis," J. Time Ser. Anal., vol. 8, no. 2, pp. 235-247, 1987.
38. S. Yakowitz, "Nonparametric density and regression estimation for Markov sequences without mixing assumptions," J. Multivariate Anal., vol. 30, pp. 124-136, 1989.
39. S. L. Zeger and B. Qaqish, "Markov regression models for time series: A quasilikelihood approach," Biometrics, vol. 44, pp. 1019-1031, 1988.