Manipulator visual servoing and tracking of fish using a genetic algorithm

Mamoru Minami, Julien Agbanhan, Toshiyuki Asakura

Research output: Contribution to journalArticlepeer-review

54 Citations (Scopus)


This paper presents the real-time visual servoing of a manipulator and its tracking strategy of a fish, by employing a genetic algorithm (GA) and the unprocessed gray-scale image termed here as `raw-image'. The raw-image is employed to shorten the control period, since it has more tolerance of contrast variations occurring within an object, and between one input image and the next one. GA is employed in a method called 1-step-GA evolution. In this way, for every generational step of the GA process, the found results, which express the deviation of the target in the camera frame, are output for control purposes. These results are then used to determine the control inputs of the PD-type controller. Our proposed GA-based visual servoing has been implemented in a real system, and the results have shown its effectiveness by successfully tracking a moving target fish.

Original languageEnglish
Pages (from-to)278-289
Number of pages12
JournalIndustrial Robot
Issue number4
Publication statusPublished - Jan 1 1999
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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