Image-based visual servoing for quadrotor helicopters using genetic algorithm

Xuesi Li, Kai Jiang, Chunlei Yang, Zhihong Wang, Xuejun Zhu, Hongbo Wang, Haobin Shi

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

3 Scopus citations

Abstract

Flying and hovering control are key technologies for the quadrotor helicopters, and could improve the performance of quadrotor helicopters. Whereas, problems of cumulative bias, low generality, high sensitivity for parameters, etc. always existing in control methods of quadrotor helicopters attract interests of many researchers. This paper puts forward an improved image-based visual servoing method with a dynamic servoing gain tuned by genetic algorithm (IBVS-GA). Complying with the under-actuated characteristics of the quadrotor helicopter, simplified IBVS model is designed where the dimension of the control parameters are reduced into four from six. The genetic algorithm is then utilized for obtaining the appropriate servoing gain value. The results of simulations and experiments demonstrate that the proposed method has better properties in efficiency than the competing methods.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Information and Automation, ICIA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1216-1221
Number of pages6
ISBN (Electronic)9781538680698
DOIs
StatePublished - Aug 2018
Event2018 IEEE International Conference on Information and Automation, ICIA 2018 - Wuyishan, Fujian, China
Duration: 11 Aug 201813 Aug 2018

Publication series

Name2018 IEEE International Conference on Information and Automation, ICIA 2018

Conference

Conference2018 IEEE International Conference on Information and Automation, ICIA 2018
Country/TerritoryChina
CityWuyishan, Fujian
Period11/08/1813/08/18

Keywords

  • Dynamic servoing gain
  • Genetic algorithm
  • Image-based visual servoing
  • Quadrotor helicopter
  • Under-actuated system

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