String shape recognition using enhanced matching method from 3D point cloud data

Tomoya Shirakawa, Takayuki Matsuno, Akira Yanou, Mamoru Minami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The deformable object such as string, cloth and paper, is soft and can change its shape easily. It is difficult for a robot to manipulate deformable object because it needs to deal with various shape. For the operation of deformable object, it is important to recognize the shape of them. In our previous research, point chain model and the string shape recognition method were proposed. Point chain model is a structure to describe a string shape by a series of connections of points. And the string shape recognition method are algorithms to recognize a string shape from 3D point cloud data and output point chain model. However, the previous method sometimes occurred misrecognition of segments. Therefore, enhanced matching method is proposed to improve recognition performance.

Original languageEnglish
Title of host publication2015 IEEE/SICE International Symposium on System Integration, SII 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages449-454
Number of pages6
ISBN (Print)9781467372428
DOIs
Publication statusPublished - Feb 10 2016
Event8th Annual IEEE/SICE International Symposium on System Integration, SII 2015 - Nagoya, Japan
Duration: Dec 11 2015Dec 13 2015

Other

Other8th Annual IEEE/SICE International Symposium on System Integration, SII 2015
CountryJapan
CityNagoya
Period12/11/1512/13/15

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

Cite this

Shirakawa, T., Matsuno, T., Yanou, A., & Minami, M. (2016). String shape recognition using enhanced matching method from 3D point cloud data. In 2015 IEEE/SICE International Symposium on System Integration, SII 2015 (pp. 449-454). [7405021] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SII.2015.7405021