An improved ant colony algorithm for UAV route planning in complex battlefield environment

Authors:
Fei Su;Yuan Li;Lincheng Shen
Affiliations:
College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

Ant colony algorithm is applied to solve UAV (Unmanned Aerial Vehicle) route planning in complex battle field environment. According to the properties of battlefield, an integrated cost estimate measure is presented, which takes the distance of UAV route and threats into account. Then a ant colony algorithm for UAV route planning is put forward to solve the problem. According to the characteristics of the UAV route planning in complex battlefield environment, state transition rules based on integrated cost estimation is designed, and the pheromone diffuse mechanism is introduced to improve the performance of algorithm. The simulation results demonstrate the feasibility and efficiency of our algorithm.