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A Clustering Approach to Path Planning for Big Groups

Author

Listed:
  • Jakub Szkandera

    (University of West Bohemia, Pilsen, Czech Republic)

  • Ondřej Kaas

    (University of West Bohemia, Pilsen, Czech Republic)

  • Ivana Kolingerová

    (University of West Bohemia, Pilsen, Czech Republic)

Abstract

The article introduces a new method of planning paths for big groups in dynamic environments represented by a graph of vertices and edges, where the edge weight as well as the graph topology may change, but the method is also applicable to environments with a different representation. The utilization of clustering enables the use of a computed path for a group of agents. In this way, a speed-up and memory savings are achieved at a cost of some path sub-optimality. Examples of proper applications of the suggested approach are crowd simulation in urban environments or path-planning-based tasks in molecular biology. The experiments showed good behaviour of the method to speed-up, relative error and online computation.

Suggested Citation

  • Jakub Szkandera & Ondřej Kaas & Ivana Kolingerová, 2019. "A Clustering Approach to Path Planning for Big Groups," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 15(2), pages 42-61, April.
    • Handle: RePEc:igg:jdwm00:v:15:y:2019:i:2:p:42-61
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