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Advances, Systems and Applications

Table 8 Experiments for Performance Comparison between PSAACO and Other Algorithms

From: Grid-Based coverage path planning with NFZ avoidance for UAV using parallel self-adaptive ant colony optimization algorithm in cloud IoT

  

BF

SP

WF

PSAACO

CPP model1

Path length[m]

308.20

314.00

296.50

288.20

 

Turning angle[deg]

630.00

548.13

720.00

495.00

 

Energy consumption[KJ]

46.77

46.03

46.97

42.11

 

Completion time[sec]

51.82

49.67

53.65

45.32

CPP model2

Path length[m]

2085.00

1793.50

1633.10

1600.00

 

Turning angle[deg]

2507.28

1771.02

2970.00

1440.00

 

Energy consumption[KJ]

286.07

239.40

241.47

211.15

 

Completion time[sec]

292.08

238.38

262.31

208.00

CPP model3

Path length[m]

2786.40

2472.90

2009.10

1917.90

 

Turning angle[deg]

3166.26

3031.02

3510.00

1890.00

 

Energy consumption[KJ]

379.11

340.28

294.58

255.94

 

Completion time[sec]

384.18

348.32

317.91

254.79