Model-based virtual visual servoing with point cloud data

Cherdsak Kingkan, Shogo Ito, Shogo Arai, Takashi Nammoto, Koichi Hashimoto

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

4 Citations (Scopus)

Abstract

In this paper, we address an issue on non-existence of a CAD model of an object in a model-based virtual visual servoing system. The approach for reconstructing a 3D model with fewer faces from point cloud data is presented. Because of a number of faces on the model surface, this reconstructed model required less rendering time than a CAD model, consequently, high speed and high accuracy model-based visual servoing can be achieved.We present the experimental results to demonstrate the effectiveness in terms of rendering time, convergence speed, and tracking speed measurements. The comparison of performances of a model-based visual servoing using different models, i.e.-CAD, Coarse mesh, Fine mesh, and Propose models, is also presented.

Original languageEnglish
Title of host publicationIROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5549-5555
Number of pages7
ISBN (Electronic)9781509037629
DOIs
Publication statusPublished - 2016 Nov 28
Event2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Korea, Republic of
Duration: 2016 Oct 92016 Oct 14

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
Volume2016-November
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
CountryKorea, Republic of
CityDaejeon
Period16/10/916/10/14

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Kingkan, C., Ito, S., Arai, S., Nammoto, T., & Hashimoto, K. (2016). Model-based virtual visual servoing with point cloud data. In IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 5549-5555). [7759816] (IEEE International Conference on Intelligent Robots and Systems; Vol. 2016-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2016.7759816