Performance Comparison of Landmark Recognition Systems for Navigating Mobile Robots

Proceedings of the 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence, AAAI 2000

Volumn , Issue , 2000, Pages 826-831

  Duckett, Tom ^a   Nehmzow, Ulrich ^b  

^a ÖREBRO UNIVERSITY   (Sweden)

^b UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN ROBOT INTERACTION; INTELLIGENT ROBOTS;

DEAD RECKONING; EMPIRICAL STUDIES; ENVIRONMENTAL FEATURES; LANDMARK RECOGNITION; MOBILE ROBOT NAVIGATION; NOMAD 200 ROBOT; PERFORMANCE COMPARISON; PERFORMANCE MEASURE; RECOGNITION SYSTEMS; SELF LOCALIZATION;

MOBILE ROBOTS;

EID: 0012348960     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. Balkenius, C., and Kopp, L. 1996. The XT-1 vision architecture. In Proc. Symposium on Image Analysis, Lund University, Sweden.
2. Carpenter, G., and Grossberg, S. 1987. ART2: Self-organization of stable category recognition codes for analog input patterns. Applied Optics 26(23).
3. Duckett, T., and Nehmzow, U. 1998. Mobile robot self-localisation and measurement of performance in middle scale environments. Robotics and Autonomous Systems 24(1-2). Online at http://www.cs.man.ac.uk/~duckettt.
4. Duckett, T., and Nehmzow, U. 1999. Knowing your place in real world environments. In Proc. EUROBOT '99, 135-142. IEEE Computer Press. Online at http://www.cs.man.ac.uk/~duckettt.
5. Fritzke, B. 1994. Growing cell structures - a self-organizing network for unsupervised and supervised learning. Neural Networks 7(9).
6. Gutmann, J.-S.; Burgard, W.; Fox, D.; and Konolige, K. 1998. An experimental comparison of localization methods. In Proc. IROS'98.
7. Hinkel, R., and Knieriemen, T. 1988. Environment perception with a laser radar in a fast moving robot. In Symposium on Robot Control (SYROCO'88).
8. Janet, J., et al. 1995. Global self-localization for autonomous mobile robots using self-organizing Kohonen neural networks. In Proc. IROS'95.
9. Kohonen, T. 1993. Self-Organization and Associative Memory, 3rd ed. Springer.
10. Kurz, A. 1996. Constructing maps for mobile robot navigation based on ultrasonic range data. IEEE Trans. Systems, Man and Cybernetics B 26(2).
11. Lee, D., and Reece, M. 1994. Quantitative evaluation of the exploration strategies of a mobile robot. In Proc. AAAI'94.
12. Moravec, H., and Elfes, A. 1985. High resolution maps from wide angle sonar. In Proc. ICRA'85.
13. Nehmzow, U., and Smithers, T. 1991. Mapbuilding using self-organising networks in really useful robots. In Proc. SAB'91.
14. Press, W.; Teukolsky, S.; Vetterling, W.; and Flannery, B. 1992. Numerical Recipes in C, 2nd. edition. Cambridge University Press.
15. Racz, J., and Dubrawski, A. 1995. Artificial neural network for mobile robot topological localization. Robotics and Autonomous Systems 16.
16. Schöner, G., and Dose, M. 1992. A dynamical systems approach to task-level system integration used to plan and control autonomous vehicle motion. Robotics and Autonomous Systems 10:253-267.
17. Smithers, T. 1995. On quantitative performance measures of robot behaviour. Robotics and Autonomous Systems 15(1-2):107-133.
18. Thrun, S. 1998. Bayesian landmark learning for mobile robot localisation. Machine Learning 33(1).
19. Yamauchi, B., and Langley, P. 1997. Place recognition in dynamic environments. J. Robotic Systems 14(2).