A recurrent neural network approach for visual servoing of manipulators

Yinyan Zhang, Shuai Li, Bolin Liao, Long Jin, Linsen Zheng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

10 Citations (Scopus)

Abstract

The control of robotic manipulators has received significant amount of attention in the control and robotics communities. In this paper, we investigate the kinematic control of a manipulator with an eye-in-hand camera, which is referred to as visual servoing. The visual servoing problem is formulated as a constrained optimization problem, which is then solved via a recurrent neural network. By this approach, the visual servoing with respect to a static point object is achieved with the feature coordinate errors in the image space converging to zero. Besides, joint angle and velocity limits of the manipulator are satisfied, which thus enhances the safety of the manipulator during the visual servoing process. The performance of the approach is guaranteed via theoretical analysis and verified via a simulative example.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Information and Automation, ICIA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages614-619
Number of pages6
ISBN (Electronic)9781538631546
DOIs
Publication statusPublished - 20 Oct 2017
Event2017 IEEE International Conference on Information and Automation, ICIA 2017 - Macau, China
Duration: 18 Jul 201720 Jul 2017

Publication series

Name2017 IEEE International Conference on Information and Automation, ICIA 2017

Conference

Conference2017 IEEE International Conference on Information and Automation, ICIA 2017
Country/TerritoryChina
CityMacau
Period18/07/1720/07/17

Keywords

  • kinematic control
  • Manipulator
  • optimization
  • recurrent neural network
  • visual servoing

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Control and Optimization
  • Modelling and Simulation

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