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

24 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 - 2006
Externally publishedYes

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Image sensors
Robots
CCD cameras
Experiments

Keywords

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

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

Cite this

Manipulation of deformable linear objects using knot invariants to classify the object condition based on image sensor information. / Matsuno, Takayuki; Tamaki, Daichi; Arai, Fumihito; Fukuda, Toshio.

In: IEEE/ASME Transactions on Mechatronics, Vol. 11, No. 4, 2006, p. 401-408.

Research output: Contribution to journalArticle

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