Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-02T18:49:44.613Z Has data issue: false hasContentIssue false

Optimal Interceptions on Two-Dimensional Grids with Obstacles

Published online by Cambridge University Press:  10 December 2007

Ki Yin Chang*
Affiliation:
(National Taiwan Ocean University, Taiwan)
Gene Eu Jan
Affiliation:
(National Taipei University, Taiwan)
Chien-Min Su
Affiliation:
(National Taiwan Ocean University, Taiwan)
Ian Parberry
Affiliation:
(University of North Texas, USA)
*

Abstract

This article presents efficient and practical methods for path planning of optimal interceptions on two-dimensional grids with obstacles, such as raster charts or non-distorted digital maps. The proposed methods search for optimal paths from sources to multiple moving-targets by a novel higher geometry wave propagation scheme in the grids, instead of the traditional vector scheme in the graphs. By introducing a time-matching scheme, the optimal interception paths from sources to all the moving-targets are obtained among the combinations with linear time and space complexities. Two optimal path planning methods for multiple one-to-one interceptions, the MIN-MAX and MIN-AVG, are applied to emulate the real routing.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Benkoski, S. J., Monticino, M. G. and Weisinger, J. R. (1991). A survey of the search theory literature. Naval Research Logistics, 38, 469494.3.0.CO;2-E>CrossRefGoogle Scholar
Chang, K. Y., Jan, G. E. and Parberry, I. (2004). A method for searching optimal routes with collision avoidance on raster charts. The Journal of Navigation, 56, 371384.CrossRefGoogle Scholar
Chimura, F. and Tokoro, M. (1994). Trailblazer search: A new method for searching and capturing moving targets, Proceedings of the National Conference on Artificial Intelligence, 2, 13471352.Google Scholar
Dawson, J. (1997). Digital charting, now and in the future. The Journal of Navigation, 52, 251255.CrossRefGoogle Scholar
Eagle, J. N. (1984). The optimal search for a moving target when the search path is constrained. Operations Research, 32, 11071115.CrossRefGoogle Scholar
Eagle, J. N. and Yee, J. R. (1990). An optimal branch-and-bound procedure for the constrained path, moving target search problem. Operations Research, 28, 110114.CrossRefGoogle Scholar
Hart, P. E., Nilsson, N. J. and Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths, IEEE Trans. on Systems Science and Cybernetics, 4(2), 100107.Google Scholar
Ishida, T. and Korf, R. E. (1995). Moving-target: A real-time search for changing goals. IEEE Trans. on Pattern Analysis and Machine Intelligence, 17, 609619.CrossRefGoogle Scholar
Jan, G. E., Chang, K. Y., Gao, S. and Parberry, I. (2005). A 4-geometry maze routing algorithm and its application on multi-terminal nets. ACM Trans. on Design Automation of Electronic Systems, 10, 116135.CrossRefGoogle Scholar
Norris, A. P. (1998). The status and future of the electronic chart. The Journal of Navigation, 51, 321326.CrossRefGoogle Scholar
Pillich, B., Pearlman, S., Chase, C. and GmbH, S. C. (2003). Real time data and ECDIS in a web-based port management package. OCEANS Proceedings, 4, 22272233.Google Scholar
Ross, M. and Dawson, R. (1994). Drift errors in search and rescue. The Journal of Navigation, 47, 369382.CrossRefGoogle Scholar
Schuster, G. M., Melnikov, G. and Katsaggelos, A. K. (1999). A review of the minimum maximum criterion for optimal bit allocation among dependent quantizers, IEEE Transactions on Multimedia, 1(1), 317.Google Scholar
Thomas, L. C. and Eagle, J. N. (1995). Criteria and approximate methods for path-constrained moving-target search problems, Naval Research Logistics, 42, 2738.3.0.CO;2-H>CrossRefGoogle Scholar