Moving discs between polygons
Identifieur interne : 001608 ( Istex/Curation ); précédent : 001607; suivant : 001609Moving discs between polygons
Auteurs : Hans Rohnert [Allemagne]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 1988.
English descriptors
- Teeft :
- Algorithm, Answer queries, Auxiliary trees, Binary search, Chain tree, Computational geometry, Constant time, Convex corner, Curve segments, Data structure, Data structures, Destination point, Edge tree, Edge weights, Endpoint, Euclidean plane, External voronoi diagram, Feasible path, Feasible paths, Final phase, Interior nodes, Line segment, Line segments, Linear time, Maximal distance, Minimal distance, Minimal edge weight, Minimum distance, Node, Obstacle space, Open line segments, Original polygons, Piano problem, Planar graph, Polygon, Polygonal region, Preprocessing, Preprocessing algorithm, Query, Query algorithm, Same component, Siam journal, Space complexity, Straight line segments, Successor relation, Technical report, Third side, Tree edges, Voronoi, Voronoi cell, Voronoi cells, Voronoi diagram, Voronoi edge, Voronoi edges, Voronoi vertices.
Abstract
Abstract: An algorithm is given for finding a collision free path for a disc between a collection of polygons having n corners in total. The polygons are fixed and can be preprocessed. One query specifies the radius r of the disc to be moved and start and destination point of the center of the disc. The answer whether a feasible path exists is given in time O(log n). Returning a feasible path is done in additional time proportional to the length of the description of the path. Preprocessing time is O(n log n) and space complexity is O(n).
Url:
DOI: 10.1007/3-540-19488-6_137
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ISTEX:DFC6AC6BB9ACFF761BF26079EB46466D2E37F4C2Le document en format XML
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<affiliation wicri:level="1"><mods:affiliation>FB 10, Universität des Saarlandes, West Germany</mods:affiliation>
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<imprint><date>1988</date>
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<profileDesc><textClass><keywords scheme="Teeft" xml:lang="en"><term>Algorithm</term>
<term>Answer queries</term>
<term>Auxiliary trees</term>
<term>Binary search</term>
<term>Chain tree</term>
<term>Computational geometry</term>
<term>Constant time</term>
<term>Convex corner</term>
<term>Curve segments</term>
<term>Data structure</term>
<term>Data structures</term>
<term>Destination point</term>
<term>Edge tree</term>
<term>Edge weights</term>
<term>Endpoint</term>
<term>Euclidean plane</term>
<term>External voronoi diagram</term>
<term>Feasible path</term>
<term>Feasible paths</term>
<term>Final phase</term>
<term>Interior nodes</term>
<term>Line segment</term>
<term>Line segments</term>
<term>Linear time</term>
<term>Maximal distance</term>
<term>Minimal distance</term>
<term>Minimal edge weight</term>
<term>Minimum distance</term>
<term>Node</term>
<term>Obstacle space</term>
<term>Open line segments</term>
<term>Original polygons</term>
<term>Piano problem</term>
<term>Planar graph</term>
<term>Polygon</term>
<term>Polygonal region</term>
<term>Preprocessing</term>
<term>Preprocessing algorithm</term>
<term>Query</term>
<term>Query algorithm</term>
<term>Same component</term>
<term>Siam journal</term>
<term>Space complexity</term>
<term>Straight line segments</term>
<term>Successor relation</term>
<term>Technical report</term>
<term>Third side</term>
<term>Tree edges</term>
<term>Voronoi</term>
<term>Voronoi cell</term>
<term>Voronoi cells</term>
<term>Voronoi diagram</term>
<term>Voronoi edge</term>
<term>Voronoi edges</term>
<term>Voronoi vertices</term>
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<front><div type="abstract" xml:lang="en">Abstract: An algorithm is given for finding a collision free path for a disc between a collection of polygons having n corners in total. The polygons are fixed and can be preprocessed. One query specifies the radius r of the disc to be moved and start and destination point of the center of the disc. The answer whether a feasible path exists is given in time O(log n). Returning a feasible path is done in additional time proportional to the length of the description of the path. Preprocessing time is O(n log n) and space complexity is O(n).</div>
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