Cloud computing based localization for mobile robot systems

Chung Ying Li, Chen-Chien James Hsu, Wei-Yen Wang, Yi Hsing Chien, I. Hsum Li

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

3 Citations (Scopus)

Abstract

A robot localization plays an important role in the field of robot navigation. One of the most commonly used localization algorithms is Monte Carlo algorithm. To improve the efficiency of robot localization, many modified algorithms have been proposed, such as Self-Adaptive Monte Carlo algorithm. However, this method requires a lot of storage space and intensive computing, especially in large environments. In recent years, because of the rapid development of cloud computing, the data can be dynamically allocated. Therefore, this paper combines the Self-Adaptive Monte Carlo Localization algorithm with cloud computing. Some experimental results illustrate the proposed architecture, which can quickly establish the map database and provide the shared map information to multiple robots. In addition, the proposed method reduces the computational load and expands the scope of activities.

Original languageEnglish
Title of host publicationCACS 2014 - 2014 International Automatic Control Conference, Conference Digest
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages238-242
Number of pages5
ISBN (Electronic)9781479945849
DOIs
Publication statusPublished - 2014 Apr 28
Event2014 International Automatic Control Conference, CACS 2014 - Kaohsiung, Taiwan
Duration: 2014 Nov 262014 Nov 28

Publication series

NameCACS 2014 - 2014 International Automatic Control Conference, Conference Digest

Other

Other2014 International Automatic Control Conference, CACS 2014
CountryTaiwan
CityKaohsiung
Period14/11/2614/11/28

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Keywords

  • Cloud computing
  • SAMCL
  • particle filter
  • robot localization

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Li, C. Y., Hsu, C-C. J., Wang, W-Y., Chien, Y. H., & Li, I. H. (2014). Cloud computing based localization for mobile robot systems. In CACS 2014 - 2014 International Automatic Control Conference, Conference Digest (pp. 238-242). [7097194] (CACS 2014 - 2014 International Automatic Control Conference, Conference Digest). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CACS.2014.7097194