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Certainty Grid Representation for Robot Navigation by a Bayesian Method

Published online by Cambridge University Press:  17 August 2017

Dong Woo Cho*
Affiliation:
Department of Mechanical Engineering, Pohang Institute of Science and Technology, P.O. Box 125, Pohang 790–600, (South Korea)

Summary

Recent development of sensor knowledge representation by the use of a certainty grid has been extensive and shown the usefulness of the grid-based concept for robot navigation.

Yet the methodology was not perfect. This paper introduces the Bayesian formula into the certainty grid representation to overcome some difficulties of ad hoc formula that has been the only way of updating the grids. The complete derivation of the proposed updating formula is given and proved to be able to accurately identify the simulated world. Also, the paper suggests two updating models: context-sensitive and context-free. Both of them were shown to be usable through simulation in real world modeling.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1990

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References

1. Moravec, H.P. and Elfes, A., “High Resolution Maps from Wide Angle SonarIEEE Inf. Conf. on Robotics and Automation, St. Louis 116121 (1985).Google Scholar
2. Moravec, H.P., “Three-Dimensional Imaging with Cheap Sonar” Autonomous Mobile Robots: Annual Report 1985 (Mobile Robot Lab., Pittsburgh, PA. Tech. rep. CMU-RI-TR-86–4, 02 1986).Google Scholar
3. Elfes, A., “Sonar-Based Real-World Mapping and NavigationIEEE Trans. RA RA-3, No. 3, 249265 (1987).Google Scholar
4. Moravec, H.P., “Sensor Fusion in Certainty Grids for Mobile RobotsAI Magazine 9, No. 2, 6174 (1988).Google Scholar
5. Stewart, K.W., “A Model-Based Approach to 3-D Imaging and Mapping UnderwaterProc. of the 7th Int. Conf. and Exhibit on Offshore Mechanics and Arctic Engineering (OMAE), Houston, Tex. 712, (1988).Google Scholar
6. Elfes, A. and Matthies, L., “Sensor Integration for Robot Navigation: Combining Sonar and Stereo Range Data in a Grid-Based Representation26th IEEE Decision and Control Conf., LA, CA 911 (1987).Google Scholar
7. Matthies, L. and Shafer, S.A., “Error Modeling in Stereo NavigationIEEE Trans. RA RA-3, No. 3, 239248 (1987).Google Scholar
8. Berger, J.O., Statistical Decision Theory and Bayesian Analysis, (Springer-Verlag, New York, 1985).Google Scholar