Education, Science, Technology, Innovation and Life
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### Establishment of UAV Path Planning Model Based on Ant Colony and Simulated Annealing Algorithm

#### Author(s)

Li Chen 1, Xueli Chen 2, Chenfa Xiao 3

#### Affiliation(s)

1 School of Mechanical Engineering, University of Jinan, Jinan, Shandong 250001
2 School of Traditional Chinese Medicine and Food Engineering, Shanxi University of Traditional Chinese Medicine, Shanxi Jinzhong 030619
3 School of Materials Science and Engineering, University of Jinan, Jinan, Shandong 250001

Li Chen

#### ABSTRACT

This paper is about the optimal allocation, optimal path planning and optmization of two kinds of UAV (SSA UAV and Radio Relay UAV). Describes the planning and allocation of unmanned aerial vehicles (UAVs) for wildfire rescue and reconnaissance operations in Australia. First of all, we build model using analytic hierarchy process (AHP) and simulated annealing algorithm to determine the constraint conditions, considering safety, capacity, economy, Victoria region of the terrain and the size of the fire, frequency and other factors, through the branch and bound method of integer to get optimal allocation of unmanned aerial vehicle (UAV) is out of the optimal route. Secondly, we use ant colony algorithm to optimize the three-dimensional path of the UAV and plan it. Finally, we use MATLAB to consistency check, to get a comparison matrix, and then the weights for each survey and plan the best path, so as to determine the optimal number of drones and combination, and analyzes the error of the model, to ensure the accuracy of the models.

#### KEYWORDS

UAV, Ant Colony Algorithm, Simulated Annealing Algorithm

#### CITE THIS PAPER

Li Chen, Xueli Chen, Chenfa Xiao. Establishment of UAV Path Planning Model Based on Ant Colony and Simulated Annealing Algorithm. Journal of Electronics and Information Science (2021) 6: 32-38. DOI: http://dx.doi.org/10.23977/jeis.2021.61005

#### REFERENCES

[1] Zhang Bo, Ye Jiawei, Hu Yucong. Application of Simulated Annealing Algorithm in Path Optimization Problem [J]. China Journal of Highway and Transport, 2004(01): 83-85.
[2] https://www.kaggle.com/carlosparadis/fires-from-space-australia-and-new-zeland? select=fire_a rc hive_M6_96619. csv
[3] Zhao Xinqu, Chen Honglin. Improvement of GM(2,1) Model Prediction Formula [J]. Journal of Wuhan University of Technology, 2006, 28(010): 125-127, 131
[4] Yu Tao. Research and Implementation of 3D UAV Path Planning Based on Improved Ant Colony Algorithm [D].