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Ant colony optimization algorithm and artificial immune system applied to a robot route

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Authors

  • J. M.S. Ribeiro
  • M. F. Silva
  • M. F. Santos
  • V. F. Vidal
  • L. M. Honorio
  • L. A.Z. Silva
  • H. B. Rezende
  • A. F. Santos Neto
  • P. Mercorelli
  • A. A.N. Pancoti

This Article aims to introduce two meta-heuristics techniques: Ant Colony Optimization (ACO) and Artificial Immune System (AIS) to find the best route for a robot. The ACO is an algorithm based on the ant food search process, and the AIS is inspired by the defending mechanism of the human organism. In order to illustrate and compare the potential of these techniques, this paper applies both techniques in a problem of determining the shortest possible route for a robot without hitting any obstacles in three different maps. According to the tests, the ACO shows better results regarding the number of iterations to reach the global optimum, while the AIS shows better results when it comes to the processing time. From the result, it can be seen that the ACO found a solution to all maps demonstrating it is an excellent choice for this problem type.

Original languageEnglish
Title of host publicationProceedings of the 2019 20th International Carpathian Control Conference, ICCC 2019
EditorsAndrzej Kot, Agata Nawrocka
Number of pages6
Place of PublicationPiscataway
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication date01.05.2019
Article number8765910
ISBN (print)978-1-7281-0703-5
ISBN (electronic)978-1-7281-0701-1 , 978-1-7281-0702-8
DOIs
Publication statusPublished - 01.05.2019
Event20st International Carpathian Control Conference - ICCC 2019 - Kraków - Wieliczka, Poland
Duration: 26.05.2019 → 29.05.2019
Conference number: 20
https://iccc.agh.edu.pl/

    Research areas

  • Ant Colony Optimization, Artificial Immune System, Heuristics Techniques, Robot
  • Engineering

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DOI

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