Path planning for robot navigation based on Cooperative Genetic Optimization

Chen Chien Hsu, Yi Chun Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Path planning investigates issues including the shortest path, obstacle avoidance, and computation efficiency, which can be regarded as an optimal problem. Taking advantage of the genetic algorithms to solve various optimal problems, this paper first proposes a Cooperative Genetic Optimization (CGO) Algorithm, including the establishment of an elite policy and larger selection region to minimize the occurrence of local optima so as to increase the speed of convergence. Based on the proposed CGO, a global path planning approach for robots is then presented. As a result, the proposed method of this paper leads to a better performance in comparison with the traditional Genetic algorithm to achieve the goal of obtaining a safer and shorter path.

Original languageEnglish
Title of host publicationProceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
PublisherIEEE Computer Society
Pages316-321
Number of pages6
ISBN (Print)9781479931064
DOIs
Publication statusPublished - 2014 Jan 1
Event11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 - Miami, FL, United States
Duration: 2014 Apr 72014 Apr 9

Publication series

NameProceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

Other

Other11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
CountryUnited States
CityMiami, FL
Period14/4/714/4/9

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Keywords

  • genetic algorithm
  • path planning
  • robots

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

Cite this

Hsu, C. C., & Liu, Y. C. (2014). Path planning for robot navigation based on Cooperative Genetic Optimization. In Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 (pp. 316-321). [6819645] (Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014). IEEE Computer Society. https://doi.org/10.1109/ICNSC.2014.6819645