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Cooperative Path Planner for UAVs Using ACO Algorithm with Gaussian Distribution Functions

  • Chi-Tsun Cheng
  • , Kia Fallahi
  • , Henry Leung
  • , Chi K. Tse

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Unmanned aerial vehicles (UAVs) are remote controlled or autonomous air vehicles. An UAV can be equipped with various types of sensors to perform life rescue missions or it can be armed with weapons to carry out stealthy attack missions. With the unmanned nature of UAVs, a mission can be taken in any hostile environment without risking the life of pilots. Among life rescue missions, the common objective is often defined as maximizing the total coverage area of the UAVs with the limited resources. When the number of UAVs increases, coordination among these UAVs becomes very complicated even for experienced pilots. In this paper, a cooperative path planner for UAVs is proposed. The path of each UAV is represented by a B-spline curve with a number of control points. The positions of these control points are optimized using an ant colony optimization algorithm (ACO) such that the total coverage of the UAVs is maximized. ©2009 IEEE.
Original languageEnglish
Title of host publication2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Pages173-176
DOIs
Publication statusPublished - May 2009
Externally publishedYes
Event2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009 - Taipei, Taiwan, China
Duration: 24 May 200927 May 2009

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
PlaceTaiwan, China
CityTaipei
Period24/05/0927/05/09

Research Keywords

  • ACO
  • B-spline
  • Coverage
  • Path planning
  • Resource management
  • UAV

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