GIPUT: Maximizing Photo Coverage Efficiency for UAV Trajectory
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-7232-2_26
Reference24 articles.
1. Chen, J., et al.: Global-and-local attention-based reinforcement learning for cooperative behaviour control of multiple uavs. IEEE Trans. Veh. Technol. (2023)
2. Dai, H., Zhang, Y., Wang, X., Liu, A.X., Chen, G.: Omnidirectional chargability with directional antennas. IEEE Trans. Mob. Comput. 23(05), 4483–4500 (2024)
3. Ebrahimi, D., Sharafeddine, S., Ho, P.H., Assi, C.: Autonomous uav trajectory for localizing ground objects: a reinforcement learning approach. IEEE Trans. Mob. Comput. 20(4), 1312–1324 (2020)
4. He, J., Li, Y., Zhang, K.: Research of uav flight planning parameters (2012)
5. Jiang, Y., Zhai, D., Yang, M., Lin, Z., Li, Y.: Non-position-based uav trajectory optimization for coverage maximization. In: Proceedings of the 5th International ACM Mobicom Workshop on Drone Assisted Wireless Communications for 5G and Beyond, pp. 67–72 (2022)
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