Distributed Reconnaissance Task Planning for Multi-UAV System
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Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-15-8155-7_178
Reference8 articles.
1. Schwarzrock, J. et al.: Solving task allocation problem in multi unmanned aerial vehicles systems using swarm intelligence. J. Eng. Appl. Artif. Intell. 72, 10–20 (2018). https://doi.org/10.1016/j.engappai.2018.03.008
2. Girard, J. et al.: Concurrent Markov decision processes for robot team learning. J. Eng. Appl. Artif. Intell. 39, 223–34 (2015). https://doi.org/10.1016/j.engappai.2014.12.007
3. . Keviczky, T. et al.: Decentralized receding horizon control and coordination of autonomous vehicle formations. J. IEEE Trans. Control Syst. Technol. 16(1), 19–33 (2007). https://doi.org/10.1109/TCST.2007.903066
4. Cai, Y. et al.: Path planning for UAV tracking target based on improved A-star algorithm.C. In: 2019 1st International Conference on Industrial Artificial Intelligence (IAI). IEEE, pp. 1–6 (2019).https://doi.org/10.1109/ICIAI.2019.8850744
5. Roberge, V. et al.: Comparison of parallel genetic algorithm and particle swarm optimization for real-time UAV path planning. J. IEEE Trans. Ind. Inf. 9(1), 132–141 (2012). https://doi.org/10.1109/TII.2012.2198665
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