A genetic algorithm-based surface segmentation method for spray painting robotics

Zhenzhou Fu, Bing Xiao, Chaofan Wu, Jia Yang

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

9 Scopus citations

Abstract

Two novel methods of complex surface segmentation in robot spray trajectory planning are developed. It is designed by using genetic algorithm. The first method is able to separate the largest patch from the surface, while the second approach is capable of dividing the surface with the smallest number of slices. Moreover, different initial triangles are selected to produce different segmentation results. This will inevitably affect the result of trajectory planning. Simulation results with the proposed approaches applied to the part of car's front are further presented to validate effectiveness of the proposed methods.

Original languageEnglish
Title of host publicationProceedings of the 29th Chinese Control and Decision Conference, CCDC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4049-4054
Number of pages6
ISBN (Electronic)9781509046560
DOIs
StatePublished - 12 Jul 2017
Externally publishedYes
Event29th Chinese Control and Decision Conference, CCDC 2017 - Chongqing, China
Duration: 28 May 201730 May 2017

Publication series

NameProceedings of the 29th Chinese Control and Decision Conference, CCDC 2017

Conference

Conference29th Chinese Control and Decision Conference, CCDC 2017
Country/TerritoryChina
CityChongqing
Period28/05/1730/05/17

Keywords

  • Genetic Algorithm
  • Patch Forming
  • Spray Trajectory Planning
  • Surface Segmentation

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