J4 ›› 2013, Vol. 31 ›› Issue (1): 66-72.

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Path Planning for UAVs Based on Improved Ant Colony Algorithm

HAN Pan1, CHEN Mou1, CHEN Shao-ong2, LIU Min2   

  1. 1. College of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;2. Key Laboratory of Optical-lectrics Control Technology, Luoyang Institute of Electro-ptical Equipment, Luoyang 471009, China
  • Received:2012-07-01 Online:2003-01-24 Published:2013-04-01

Abstract:

Aiming at the wide use of the UAV (Unmanned Aerial Vehicles) in designated place to perform reconnaissance, detection or patrol mission, etc, the tasks cost model of the path planning of UAVs is transformed into the traveling salesman problem. The improved ant colony algorithm is employed to complete the path planning of UAV. To overcome the problem of easy convergence to the local optimum in the last stage for the basic ant colony algorithm, the cross tabu search strategy is introduced to improve the basic ant colony algorithm. The simulation study is presented to prove the effectiveness of the developed path planning method based on the improved ant aolony alg
orithm. The simulation results show that the developed algorithm can improve the optimization ability of path planning for UAV.

Key words: unmanned aerial vehicles(UAV), path planning, ant colony algorithm, tabu search, travelling salesman problem (TSP)

CLC Number: 

  • TP391