Abstract
We develop algorithms and data structures for the approximate Euclidean shortest path problem amid a set P of k convex obstacles in ℝ2 and ℝ3, with a total of n faces. The running time of our algorithms is linear in n, and the size and query time of our data structure are independent of n. We follow a "core-set" based approach, i.e., we quickly compute a small sketch Q of P whose size is independent of n and then compute approximate shortest paths with respect to Q. Copyright © by SIAM.
Cite
CITATION STYLE
Agarwal, P. K., Sharathkumar, R., & Yu, H. (2009). Approximate Euclidean shortest paths amid convex obstacles. In Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 283–292). Association for Computing Machinery. https://doi.org/10.1137/1.9781611973068.32
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