A Neural Network Unmanned Aerial Vehicle Conflict Resolution Method Based on Bat Algorithm - Xiongfengshi, Xie; Hongwei, Shi (2024 IEEE 2nd International Conference on Control, Electronics and Computer Technology (ICCECT), 2024)
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.