A Neural Network Unmanned Aerial Vehicle Conflict Resolution Method Based on Bat Algorithm

In the context of airspace integration, to ensure the safety of unmanned aerial vehicles (UAVs), a method for resolving UAV conflicts based on the optimization of bat algorithm and neural network is proposed. This method combines the advantages of both techniques. The neural network output controls...

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Bibliographic Details
Published in2024 IEEE 2nd International Conference on Control, Electronics and Computer Technology (ICCECT) pp. 412 - 416
Main Authors Xiongfengshi, Xie, Hongwei, Shi
Format Conference Proceeding
LanguageEnglish
Published IEEE 26.04.2024
Subjects
Autonomous aerial vehicles
bat algorithm
conflict resolution
Convergence
Encoding
neural network
Neural networks
Optimization
Safety
Trajectory
UAV
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DOI10.1109/ICCECT60629.2024.10545723

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Summary:In the context of airspace integration, to ensure the safety of unmanned aerial vehicles (UAVs), a method for resolving UAV conflicts based on the optimization of bat algorithm and neural network is proposed. This method combines the advantages of both techniques. The neural network output controls the UAV's current step-length release strategy, while encoding the parameters of the neural network as bat coordinates for global optimization. Finally, the optimized release strategy is outputted to form a release trajectory. Through simulation experiments, it is verified that this release model can provide high-quality release trajectories for both conflicting UAVs. The model is simple and efficient, ensuring rapid release of UAVs when encountering conflict threats.
DOI:10.1109/ICCECT60629.2024.10545723