Publication detail

Computational Geometry Data Structures in Logistics and Navigation Tasks

ŠEDA, M. ŠEDA, P.

Original Title

Computational Geometry Data Structures in Logistics and Navigation Tasks

Type

conference paper

Language

English

Original Abstract

Computational geometry data structures have many applications, such as network optimisation, location tasks, but they can also be used in robot motion planning when a path of the shortest length must be found between the start and target positions that guarantee movements without the risk of collisions with obstacles. The paper deals with visibility graphs, strip and cell decompositions, Voronoi diagrams and compares their properties and efficiency in the investigated area. Since cell decomposition-based approaches give exponential complexity depending on the number of cells, and the knowledge base makes it possible to reduce it mostly only insignificantly, Voronoi diagrams with their polynomial complexity are more efficient for large instances. In addition, their generalized version allows them to generate smooth trajectories.

Keywords

Voronoi diagram, robot motion planning, celland strip decompositions, case-based reasoning

Authors

ŠEDA, M.; ŠEDA, P.

Released

15. 10. 2020

Publisher

IEEE

Location

online

ISBN

978-1-7281-9281-9

Book

2020 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)

Pages from

179

Pages to

184

Pages count

6

URL

BibTex

@inproceedings{BUT165612,
  author="Miloš {Šeda} and Pavel {Šeda}",
  title="Computational Geometry Data Structures in Logistics and Navigation Tasks",
  booktitle="2020 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)",
  year="2020",
  pages="179--184",
  publisher="IEEE",
  address="online",
  doi="10.1109/ICUMT51630.2020.9222453",
  isbn="978-1-7281-9281-9",
  url="https://ieeexplore.ieee.org/document/9222453"
}