Fish-catching by robot using prediction neural network - Reducing steady-state error to zero

Mamoru Minami, Tongxiao Zhang

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

Abstract

This paper presents a method to predict a fish motion by Neural Network (N.N.) with on-line learning when a robot is pursuing fish-catching by a net at hand through hand-eye robot visual servoing. We have learned by previous experiments that fish is much smarter than a robot controlled by visual servoing whose escaping strategy is to make a steady state distance error between the net at robot's hand and the fish. To overcome the fish's escaping strategy we propose prediction servoing utilizing estimated future fish position by on-line adjusting N.N.. The effectiveness have been proven through visual servoing and fish catching experiments.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Pages5020-5025
Number of pages6
Publication statusPublished - Dec 1 2009
Externally publishedYes
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
Duration: Aug 18 2009Aug 21 2009

Publication series

NameICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
CountryJapan
CityFukuoka
Period8/18/098/21/09

Keywords

  • Fish-catching
  • Neural network

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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  • Cite this

    Minami, M., & Zhang, T. (2009). Fish-catching by robot using prediction neural network - Reducing steady-state error to zero. In ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings (pp. 5020-5025). [5334628] (ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings).