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Online Scheduling for Aerial Recovery of Multiple UAVs

  • School of Astronautics, Harbin Institute of Technology
  • China Aerospace Science and Technology Corporation
  • Expace Technology Co. Ltd

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

Abstract

This paper studies online scheduling for recovering unmanned aerial vehicles (UAVs) in the air. We propose a genetic algorithm (GA) to obtain the schedule for recovering multiple UAVs. In real-world environment, the optimal recovery sequence needs to be regenerated when some UAVs leave the recovery sequence due to emergency or new UAVs arrive and join for recovery. An elite seeding strategy is developed and then integrated into the GA to update the recovery sequence. The simulation results show that the GA with elite seeding strategy can quicken the iteration process of finding the best recovery sequence in dynamic scenarios.

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages508-512
Number of pages5
ISBN (Electronic)9781728137926
DOIs
StatePublished - Oct 2019
Externally publishedYes
Event2019 IEEE International Conference on Unmanned Systems, ICUS 2019 - Beijing, China
Duration: 17 Oct 201919 Oct 2019

Publication series

NameProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

Conference

Conference2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Country/TerritoryChina
CityBeijing
Period17/10/1919/10/19

Keywords

  • aerial recovery
  • elite seeding strategy
  • online scheduling
  • unmanned aerial vehicles

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