Improved eye-vergence visual servoing system in longitudinal direction with RM-GA

Yejun Kou, Hongzhi Tian, Mamoru Minami, Takayuki Matsuno

Research output: Contribution to journalArticle

Abstract

Visual servoing is a control method to manipulate the motion of the robot using visual information, which aims to realize “working while watching.” However, the visual servoing towards moving target with hand–eye cameras fixed at hand is inevitably affected by hand dynamical oscillation. To overcome this defect of the hand–eye fixed camera system, an eye-vergence system has been put forward, where the pose of the cameras could be rotated to observe the target object. The visual servoing controllers of hand and eye-vergence are installed independently, so that it can observe the target object at the center of camera images through eye-vergence function. In this research, genetic algorithm (GA) is used as a pose tracking method, which is called “Real-Time Multi-step GA(RM-GA),” solves on-line optimization problems for 3D visual servoing. The performances of real-time object tracking using eye-vergence system and “RM-GA” method have been examined, and also the pose tracking accuracy has been verified.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalArtificial Life and Robotics
DOIs
Publication statusAccepted/In press - Nov 11 2017

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Keywords

  • Eye-vergence
  • Longitudinal
  • Optimization
  • Real-time Multi-step GA
  • Visual servoing

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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