Vision-based Control Approach for Generalized Planar Parallel Robots

Xueling Luo, Xiaodong Jin, Dan Zhang, Qi Zou

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

Abstract

Generalized parallel mechanisms become the refinement research result of the parallel mechanism study to overcome limits such as small rotational performance or low task specificity of traditional parallel mechanisms. Towards an effective control scheme for generalized parallel mechanisms is the key to promoting its future application. This paper is dedicated to visual-based control modelling of planar parallel robots. To overcome the challenge of end-effect pose estimation for the parallel mechanism, the control scheme is able to minimize the error of the end-effect of the mechanism through information obtained from a fixed visual system. The simulation and experiment results show the time efficiency and accuracy of the proposed control scheme that able to stabilize the system in a short time during the motion control.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Automation, Control and Robotics Engineering, CACRE 2020
EditorsFumin Zhang, Lu Liu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages216-220
Number of pages5
ISBN (Electronic)9781728198880
DOIs
Publication statusPublished - Sept 2020
Externally publishedYes
Event5th International Conference on Automation, Control and Robotics Engineering, CACRE 2020 - Dalian, China
Duration: 19 Sept 202020 Sept 2020

Publication series

NameProceedings - 5th International Conference on Automation, Control and Robotics Engineering, CACRE 2020

Conference

Conference5th International Conference on Automation, Control and Robotics Engineering, CACRE 2020
Country/TerritoryChina
CityDalian
Period19/09/2020/09/20

Keywords

  • 3D pose measurement
  • generalized parallel mechanisms
  • motion control
  • vision-based control scheme

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering
  • Computational Mathematics
  • Control and Optimization

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