Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (12): 3029-3038.doi: 10.13229/j.cnki.jdxbgxb20210403

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Improved algorithm of UAV search based on electric field model and simulation analysis

Hang ZHU(),Han-bo YU,Jia-hui LIANG,Hong-ze LI   

  1. College of Mechanical and Aerospace Engineering，Jilin University，Changchun 130022，China
  • Received:2021-04-25 Online:2022-12-01 Published:2022-12-08

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Abstract:

An improved ant colony algorithm based on physical electric field model was proposed in order to solve the problem of a single UAV visual navigation for ground moving target search. The complex search area was defined， the grid was divided， and the grid node was defined as an activable pheromone point. The ant colony algorithm was optimized based on the potential field rules of the physical electric field model， and the probability model was introduced. An improved particle swarm optimization algorithm for UAV search based on electric field model was established to control the pose and speed of UAV. The simulation results show that the average success rate of the improved ant colony algorithm for searching moving targets is 67.3%， and the average operation time of the example is 8.33 s. The simulation results show that the improved ant colony algorithm has higher success rate and less time-consuming than the particle swarm optimization algorithm.

Key words: automatic control technology, unmanned aerial vehicle （UAV） search, physical electric field model, ant colony algorithm, grid method

CLC Number: 

  • V249

Fig.1

Pheromone point diagram"

Fig.2

Area where the drone will go next"

Fig.3

Algorithm flow chart"

Fig.4

Robot will walk in a straight line on the way to escape"

Fig.5

Robot won't turn back on its way to escape"

Fig.6

Robot will turn back on its way to escape"

Fig.7

Comparison of algorithm success times"

Table 1

Comparison of average time of algorithm"

机器人行走方式粒子群算法时间/s优化算法时间/s

直线

不折返

折返

15.25

21.5

22.5

5.5

9.0

10.5

Fig.8

Comparison of search area with time in three cases"

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