Swarm Intelligent Route Planning of UAV with Elastic Track Correction

Liu Weitong, Lou Wenzhong, Wang Jinkui, Zhao Yueceng

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

1 Citation (Scopus)

Abstract

Main purpose of UAV path planning are shorten the distance, avoid flight threats and obstacles. Planning feasible path intervals is the basis of path planning. In long-distance, multi-obstacle path planning, it is more important to plan a reasonable distance and sufficient safety path. Therefore, aiming at the problem of complex track constraints in long-distance and multi-obstacle path planning, a new method of track initialization and adjustment named elastic track correction is proposed to make up for the limitations of current track initialization and solution space. Using wolf pack intelligence algorithm as validation algorithm, this paper compares the effectiveness of elastic track correction mechanism with that of general planning method, which proves that adding elastic correction mechanism to track planning algorithm can effectively improve the reliability of track planning, and can get a feasible solution of lower cost function.

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages239-244
Number of pages6
ISBN (Electronic)9781728137926
DOIs
Publication statusPublished - Oct 2019
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

  • Swarm intelligence
  • Track Correction
  • UAV track planning
  • Wolf pack algorithm

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