Vision-based multi-point sensing for corridor navigation of Autonomous Indoor Vehicle

Djoko Purwanto, Muhammad Rivai, Hendawan Soebhakti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Autonomous Indoor Vehicle (AIV) is used for various purposes so it can reduce human workload. This study aims to develop a corridor navigation system for AIV that utilizes vision-based multi point sensing. Multi-point sensing techniques on floor and corridor areas are used to detect obstacle-free areas and estimate the direction of AIV. Area detection and direction estimation are used as input information of navigation algorithm based on a fuzzy inference system to control AIV movement. The results of the experiments show that AIV can run along the corridor with the largest mean error of 6.49% with respect the centerline of the corridor.

Original languageEnglish
Title of host publicationICECOS 2017 - Proceeding of 2017 International Conference on Electrical Engineering and Computer Science
Subtitle of host publicationSustaining the Cultural Heritage Toward the Smart Environment for Better Future
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages67-70
Number of pages4
ISBN (Electronic)9781479976751
DOIs
Publication statusPublished - 2017
Event2017 International Conference on Electrical Engineering and Computer Science, ICECOS 2017 - Palembang, Indonesia
Duration: 22 Aug 201723 Aug 2017

Publication series

NameICECOS 2017 - Proceeding of 2017 International Conference on Electrical Engineering and Computer Science: Sustaining the Cultural Heritage Toward the Smart Environment for Better Future

Conference

Conference2017 International Conference on Electrical Engineering and Computer Science, ICECOS 2017
Country/TerritoryIndonesia
CityPalembang
Period22/08/1723/08/17

Keywords

  • autonomous vehicle
  • corridor navigation
  • vision-based sensing

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