Path following for mobile robots by an image-based multilayered neural network controller

Hikaru Fujioka, Tatsuya Kato, Keigo Watanabe

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

This paper proposes an image-based visual servoing (IBVS) method for making a mobile robot follow a straight line path. The IBVS seems to be a human-like approach in the viewpoint that it controls robots based on the information of camera images without using the position of the robots. In order to determine the control input from the image information, a multilayered neural network-based controller that mimics the human brain is designed. A training method for the controller uses a back-propagation algorithm. The proposed method is evaluated by some simulations.

Original languageEnglish
Pages1306-1309
Number of pages4
Publication statusPublished - Jan 1 2013
Event2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan
Duration: Sep 14 2013Sep 17 2013

Other

Other2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013
CountryJapan
CityNagoya
Period9/14/139/17/13

Keywords

  • Image-based visual servoing
  • Multilayered neural network
  • Path following

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Fujioka, H., Kato, T., & Watanabe, K. (2013). Path following for mobile robots by an image-based multilayered neural network controller. 1306-1309. Paper presented at 2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013, Nagoya, Japan.