Open Access
| Issue |
MATEC Web Conf.
Volume 355, 2022
2021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
|
|
|---|---|---|
| Article Number | 03002 | |
| Number of page(s) | 7 | |
| Section | Computing Methods and Computer Application | |
| DOI | https://doi.org/10.1051/matecconf/202235503002 | |
| Published online | 12 January 2022 | |
- Wang, Q., Liu, M., Ren, J., et al. (2019) Overview of common algorithms for UAV path planning. Journal of Jilin University (Information Science Edition), 37: 58-67. [Google Scholar]
- Cekmez, U., Ozsiginan, M., Sahingoz, O. K. (2016) Multi-colony ant optimization for UAV path planning with obstacle avoidance, In: 2016 International Conference on Unmanned Aircraft Systems. Arlington. pp. 47-52. [CrossRef] [Google Scholar]
- Hu, T. (2019) Research on 3D surveillance trajectory planning for small UAV based on bio-inspired algorithms. Dissertation of Chongqing University of Posts and Telecommunications, 41-50. [Google Scholar]
- Li, X., Wei, R., Zhang, Q., et al. (2017) A path planning for UAVs in urban building areas based on cellular ant colony algorithm. Journal of Air Force Engineering University (Natural Science Edition), 18: 19-23. [Google Scholar]
- Xing, D., Zhen, Z., Zhou, C. et al. (2019) Cooperative search of UAV swarm based on ant colony optimization with artificial potential field. Transactions of Nanjing University of Aeronautics and Astronautics, 36: 912-918. [Google Scholar]
- Li, X., Ma, R., Zhang, S., et al. (2020) Improved design of ant colony algorithm and its application in path planning. Acta Aeronautica et Astronautica Sinica, 41: 213-219. [Google Scholar]
- Liu, R., Yang, F., Zhang, H. (2018) Path planning for UAV based on improved chaotic ant colony algorithm. Command Information System and Technology, 9: 41-48. [Google Scholar]
- Xia, G., Han, Z., Zhao, B., et al. (2019) Unmanned surface vessel path planning based on quantum ant colony algorithm. Journal of Harbin Engineering University, 40: 1263-1268. [Google Scholar]
- Jiao, Y. (2019) Research on path planning of UAV based on improved ant colony algorithm. Ship Electronic Engineering, 39: 41-45. [Google Scholar]
- Wei, J., Wang, J., Wang, J., et al. (2020) 3D path planning based on improved ant colony algorithm. Computer Engineering and Applications, 56: 217-223. [Google Scholar]
- Gao, Y., Chen, X., Zhou, S., et al. (2016) Planning based on improved ant colony algorithm for multiple batches collaborative three-dimensional track. Journal of Northwestern Polytechnical University, 34: 41-46. [Google Scholar]
- Jie, D., Tang, X., Chen, J., et al. (2020) Research on conflict resolution technology of multi-UAV based on improved ant colony algorithm. Journal of Wuhan University of Technology (Transportation Science & Engineering), 44: 141-147. [Google Scholar]
- Tang, X., Ji, X., Li, T. (2020) Key technology in multi-UAV conflict detection and resolution strategy. Transactions of Nanjing University of Aeronautics and Astronautics, 37: 175-186. [Google Scholar]
- Wu, X., Jia, Y., Zhang, J., et al. (2018) Simulation study of UAV conflict resolution based on an improved ant colony algorithm. Journal of Hebei University of Science and Technology, 39: 166-175. [Google Scholar]
- Ouyang, Z., Guo, Q. (2018) Penetration route planning of UAV based on improved ant colony algorithm. Modern Defense Technology, 46: 74-78. [Google Scholar]
- Zhao, H., Zhou, H., Wang, S. (2021) Quantum particle swarm optimization algorithm of three-dimensional path planning of unmanned aerial vehicle. Aerospace Control, 39: 40-45. [Google Scholar]
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