Cooperative path planner for UAVs using ACO algorithm with gaussian distribution functions

Chi Tsun Cheng, Kia Fallahi, Henry Leung, Chi Kong Tse

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

21 Citations (Scopus)


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.
Original languageEnglish
Title of host publication2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009
Number of pages4
Publication statusPublished - 26 Oct 2009
Event2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009 - Taipei, Taiwan
Duration: 24 May 200927 May 2009


Conference2009 IEEE International Symposium on Circuits and Systems, ISCAS 2009


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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this