A Clustering Approach to Path Planning for Big Groups
| Autor: | Ondřej Kaas, Ivana Kolingerová, Jakub Szkandera |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
050210 logistics & transportation
Computer science 05 social sciences 020207 software engineering 02 engineering and technology computer.software_genre Hardware and Architecture 0502 economics and business 0202 electrical engineering electronic engineering information engineering Data mining Motion planning Cluster analysis computer Software |
| Zdroj: | International Journal of Data Warehousing and Mining. 15:42-61 |
| ISSN: | 1548-3932 1548-3924 |
| DOI: | 10.4018/ijdwm.2019040103 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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