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ABSTRACT
We present a practical algorithm for finding minimum-length paths between points in the Euclidean plane with (not necessarily convex) polygonal obstacles. Prior to this work, the best known algorithm for finding the shortest path between two points in the plane required &OHgr;(n2 log n) time and O(n2) space, where n denotes the number of obstacle edges. Assuming that a triangulation or a Voronoi diagram for the obstacle space is provided with the input (if is not, either one can be precomputed in O(n log n) time), we present an O(kn) time algorithm, where k denotes the number of “islands” (connected components) in the obstacle space. The algorithm uses only O(n) space and, given a source point s, produces an O(n) size data structure such that the distance between s and any other point x in the plane (x) is not necessarily an obstacle vertex or a point on an obstacle edge) can be computed in O(1) time. The algorithm can also be used to compute shortest paths for the movement of a disk (so that optimal movement for arbitrary objects can be computed to the accuracy of enclosing them with the smallest possible disk).
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David Eppstein , Jeff Erickson, Raising roofs, crashing cycles, and playing pool: applications of a data structure for finding pairwise interactions, Proceedings of the fourteenth annual symposium on Computational geometry, p.58-67, June 07-10, 1998, Minneapolis, Minnesota, United States
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Danny Z. Chen , Kevin S. Klenk , Hung-Yi T. Tu, Shortest path queries among weighted obstacles in the rectilinear plane, Proceedings of the eleventh annual symposium on Computational geometry, p.370-379, June 05-07, 1995, Vancouver, British Columbia, Canada
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