Manipulation of deformable linear objects using knot invariants to classify the object condition based on image sensor information

Takayuki Matsuno, Daichi Tamaki, Fumihito Arai, Toshio Fukuda

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Using a topological model and knot theory, we propose a method for describing the condition of a rope. We also propose a recognition method based on the image information obtained from the charge-coupled device cameras to obtain the structure of the rope when manipulated by a robot. This method will help solve the difficulties of robots manipulating deformable objects by providing a theoretical framework of error recovery for deformable object manipulation. We confirm the effectiveness of the methods through experiments.

Original languageEnglish
Pages (from-to)401-408
Number of pages8
JournalIEEE/ASME Transactions on Mechatronics
Volume11
Issue number4
DOIs
Publication statusPublished - Dec 1 2006
Externally publishedYes

Keywords

  • Deformable object manipulation
  • Graph structure
  • Knot invariant
  • Shape recognition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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