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Kinetic Geodesic Voronoi Diagrams in a Simple Polygon

Authors Matias Korman, André van Renssen, Marcel Roeloffzen, Frank Staals

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Author Details

Matias Korman
  • Department of Computer Science, Tufts University, Medford, MA, USA
André van Renssen
  • School of Computer Science, University of Sydney, Australia
Marcel Roeloffzen
  • Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands
Frank Staals
  • Department of Information and Computing Sciences, Utrecht University, The Netherlands


We would like to thank Man-Kwun Chiu and Yago Diez for interesting discussions during the initial stage of this research.

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Matias Korman, André van Renssen, Marcel Roeloffzen, and Frank Staals. Kinetic Geodesic Voronoi Diagrams in a Simple Polygon. In 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 168, pp. 75:1-75:17, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)


We study the geodesic Voronoi diagram of a set S of n linearly moving sites inside a static simple polygon P with m vertices. We identify all events where the structure of the Voronoi diagram changes, bound the number of such events, and then develop a kinetic data structure (KDS) that maintains the geodesic Voronoi diagram as the sites move. To this end, we first analyze how often a single bisector, defined by two sites, or a single Voronoi center, defined by three sites, can change. For both these structures we prove that the number of such changes is at most O(m³), and that this is tight in the worst case. Moreover, we develop compact, responsive, local, and efficient kinetic data structures for both structures. Our data structures use linear space and process a worst-case optimal number of events. Our bisector KDS handles each event in O(log m) time, and our Voronoi center handles each event in O(log² m) time. Both structures can be extended to efficiently support updating the movement of the sites as well. Using these data structures as building blocks we obtain a compact KDS for maintaining the full geodesic Voronoi diagram.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • kinetic data structure
  • simple polygon
  • geodesic voronoi diagram


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