Localization of freeform surface workpiece with particle swarm optimization algorithm

Ce Han, Dinghua Zhang, Baohai Wu, Kun Pu, Ming Luo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

A localization method for freeform surface workpiece with particle swarm optimization (PSO) algorithm is proposed in this paper. This study is the first attempt to use PSO as a matching algorithm in localization based on in situ measuring technology. The performance of the algorithm is studied by a set of simulations and optimal parameters settings are given. To test the performance of PSO and compare it with the classical Iterative Closest Point (ICP) algorithm, a blade model and a free-form surface model are used in this study. Simulation results show that PSO with the proposed parameter settings is appropriate to the localization of different freeform surface workpieces with high accuracy and not dependent on pre-localization condition. This study proves that PSO is a new effective algorithm for the localization of freeform surface workpiece because of its advantage of high global search ability over most existing algorithms.

Original languageEnglish
Title of host publicationProceedings of the 2014 International Conference on Innovative Design and Manufacturing, ICIDM 2014
EditorsYong Zeng, Yong Chen, Yong Chen, Sofiane Achiche, Weiming Shen, Anjali Awasthi, Chih-Hsing Chu, Caterina Rizzi, Chun Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages47-52
Number of pages6
ISBN (Electronic)9781479962709
DOIs
StatePublished - 26 Sep 2014
Event2014 International Conference on Innovative Design and Manufacturing, ICIDM 2014 - Montreal, Canada
Duration: 13 Aug 201415 Aug 2014

Publication series

NameProceedings of the 2014 International Conference on Innovative Design and Manufacturing, ICIDM 2014

Conference

Conference2014 International Conference on Innovative Design and Manufacturing, ICIDM 2014
Country/TerritoryCanada
CityMontreal
Period13/08/1415/08/14

Keywords

  • localization
  • matching algorithm
  • parameter settings
  • particle swarm optimization

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