Citation: | WANG F Y,MENG X Y,ZHANG H K. UAV three-dimensional path planning based on ε-level bat algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(5):1593-1603 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0502 |
To address the problem of complex terrain environment and various threats and constraints, this article proposes a path planning algorithm for UAV based on
[1] |
SANTOSO F, GARRATT M, ANAVATTI S. State-of-the-art intelligent flight control systems in unmanned aerial vehicles[J]. IEEE Transactions on Automation Science and Engineering, 2018, 15(2): 613-627. doi: 10.1109/TASE.2017.2651109
|
[2] |
ZHAO Y J, ZHENG Z, LIU Y. Survey on computational-intelligence-based UAV path planning[J]. Knowledge-Based Systems, 2018, 158: 54-64. doi: 10.1016/j.knosys.2018.05.033
|
[3] |
LIU H, ZHANG N, LI Q. UAV path planning based on an improved ant colony algorithm[C]//Proceedings of 2021 4th International Conference on Intelligent Autonomous Systems (ICoIAS). Piscataway: IEEE Press, 2021: 357-360.
|
[4] |
陈侠, 刘奎武, 毛海亮. 基于APF-RRT算法的无人机航迹规划[J]. 电光与控制, 2022, 29(5): 17-22.
CHEN X, LIU K W, MAO H L. The path planning of UAV based on APF-RRT algorithm[J]. Electronics Optics & Control, 2022, 29(5): 17-22(in Chinese).
|
[5] |
赵红超, 周洪庆, 王书湖. 无人机三维航迹规划的量子粒子群优化算法[J]. 航天控制, 2021, 39(1): 40-45.
ZHAO H C, ZHOU H Q, WANG S H. Quantum particle swarm optimization algorithm of three-dimensional path planning of unmanned aerial vehicle[J]. Aerospace Control, 2021, 39(1): 40-45(in Chinese).
|
[6] |
SHIVGAN R, DONG Z. Energy-efficient drone coverage path planning using genetic algorithm[C]//Proceedings of 2020 IEEE 21st International Conference on High Performance Switching and Routing (HPSR). Piscataway: IEEE Press, 2020: 1-6.
|
[7] |
汤安迪, 韩统, 徐登武, 等. 混沌多精英鲸鱼优化算法[J]. 北京航空航天大学学报, 2021, 47(7): 1481-1494.
TANG A D, HAN T, XU D W, et al. Chaotic multi-leader whale optimization algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(7): 1481-1494(in Chinese).
|
[8] |
GHAMBARI S, LEPAGNOT J, JOURDAN L, et al. UAV path planning in the presence of static and dynamic obstacles[C]//Proceedings of 2020 IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway: IEEE Press, 2020, 465-472.
|
[9] |
高阳阳, 余敏建, 韩其松, 等. 基于改进共生生物搜索算法的空战机动决策[J]. 北京航空航天大学学报, 2019, 45(3): 429-436.
GAO Y Y, YU M J , HAN Q S, et al. Air combat maneuver decision-making based on improved symbiotic organisms search algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(3): 429-436(in Chinese).
|
[10] |
JAMSHIDI V, NEKOUKAR V, REFAN M H. Real time UAV path planning by parallel grey wolf optimization with align coefficient on CAN bus[J]. Cluster Computing-The Journal of Networks Software Tools and Applications, 2021, 24(3): 2495-2509.
|
[11] |
YANG X. A new metaheuristic bat-inspired algorithm[C]//Proceedings of Nature Inspired Cooperative Strategies for Optimization(NICSO 2010). Berlin: Springer, 2010: 65-74.
|
[12] |
GANDOMI A, YANG X. Chaotic bat algorithm[J]. Journal of Computational Science, 2014, 5(2): 224-232. doi: 10.1016/j.jocs.2013.10.002
|
[13] |
LIU Q, WU L, XIAO W S, et al. A novel hybrid bat algorithm for solving continuous optimization problems[J]. Applied Soft Computing, 2018, 73: 67-82. doi: 10.1016/j.asoc.2018.08.012
|
[14] |
RAUF H, MALIK S, SHOAIB U, et al. Adaptive inertia weight bat algorithm with sugeno-function fuzzy search[J]. Applied Soft Computing, 2020, 90: 106159. doi: 10.1016/j.asoc.2020.106159
|
[15] |
LYU S L, LI Z, HUANG Y L, et al. Improved self-adaptive bat algorithm with step-control and mutation mechanisms[J]. Journal of Computational Science, 2019, 30: 65-78. doi: 10.1016/j.jocs.2018.11.002
|
[16] |
YANG X, GANDOMI A. Bat algorithm: a novel approach for global engineering optimization[J]. Engineering Computations, 2012, 29(5): 464-483. doi: 10.1108/02644401211235834
|
[17] |
OSABA E, YANG X, DIAZ F, et al. An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems[J]. Engineering Applications of Artificial Intelligence, 2016, 48: 59-71. doi: 10.1016/j.engappai.2015.10.006
|
[18] |
TALBI N. Design of fuzzy controller rule base using bat algorithm[J]. Energy Procedia, 2019, 162: 241-250. doi: 10.1016/j.egypro.2019.04.026
|
[19] |
HASANÇEBI O, TEKE T, PEKCAN O. A bat-inspired algorithm for structural optimization[J]. Computers & Structures, 2013, 128: 77-90.
|
[20] |
WANG G G, CHU H C, SEYEDALI M. Three-dimensional path planning for UCAV using an improved bat algorithm[J]. Aerospace Science and Technology, 2016, 49: 231-238. doi: 10.1016/j.ast.2015.11.040
|
[21] |
HOLUB J, FOO J, KILIVARAPU V, et al. Three dimensional multi-objective UAV path planning using digital pheromone particle swarm optimization[C]//Proceedings of 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Reston: AIAA, 2012: 1525.
HOLUB J, FOO J, KILIVARAPU V, et al. Three dimensional multi-objective UAV path planning using digital pheromone particle swarm optimization[C]//Proceedings of 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Reston: AIAA, 2012: 1525.
|
[22] |
DADGAR M, JAFARI S, HAMZEH A. A PSO-based multi-robot cooperation method for target searching in unknown environments[J]. Neurocomputing, 2016, 177: 62-74. doi: 10.1016/j.neucom.2015.11.007
|
[23] |
TAKAHAMA T, SAKAI S. Constrained optimization by the ε constrained differential evolution with an archive and gradient-based mutation[C]//Proceedings of IEEE Congress on Evolutionary Computation. Piscataway: IEEE Press, 2010: 1-9.
|
[24] |
TAKAHAMA T, SAKAI S. Solving constrained optimization problems by the ε constrained particle swarm optimizer with adaptive velocity limit control[C]//Proceedings of IEEE Conference on Cybernetics & Intelligent Systems. Piscataway: IEEE Press, 2006: 1-7.
TAKAHAMA T, SAKAI S. Solving constrained optimization problems by the ε constrained particle swarm optimizer with adaptive velocity limit control[C]//Proceedings of IEEE Conference on Cybernetics & Intelligent Systems. Piscataway: IEEE Press, 2006: 1-7.
|
[25] |
WANG L, LI P. An effective differential evolution with level comparison for constrained engineering design[J]. Structural and Multidisciplinary Optimization, 2010, 41(6): 947-963. doi: 10.1007/s00158-009-0454-5
|
[26] |
ALLAIRE FCJ, TARBOUCHI M, LABONTÉ G, et al. Real-time UAV path-terrain collision evaluation on FPGA[C]//Proceedings of 2018 4th International Conference on Optimization and Applications (ICOA). Piscataway: IEEE Press, 2018: 1-5.
ALLAIRE FCJ, TARBOUCHI M, LABONTÉ G, et al. Real-time UAV path-terrain collision evaluation on FPGA[C]//Proceedings of 2018 4th International Conference on Optimization and Applications (ICOA). Piscataway: IEEE Press, 2018: 1-5.
|
[27] |
SHANMUGAVEL M, TSOURDOS A, ZBIKOWSKI R, et al. Path planning of multiple UAVs using dubins sets[C]//Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit. Reston: AIAA, 2005: 5827.
SHANMUGAVEL M, TSOURDOS A, ZBIKOWSKI R, et al. Path planning of multiple UAVs using dubins sets[C]//Proceedings of AIAA Guidance, Navigation, and Control Conference and Exhibit. Reston: AIAA, 2005: 5827.
|