Multiple-UAV Path Planning in Obstacle Environments with Evolutionary Computation
DOI:
https://doi.org/10.15837/ijccc.2025.4.6847Keywords:
unmanned aerial vehicles, 5g networks, route planning, genetic algorithm, particle swarm optimizationAbstract
Broadcasting to various devices is a critical requirement when applying 5G and B5G networks. Unmanned aerial vehicles (UAVs) are expected to facilitate wireless 5G connection to remote areas with high data transmission speed. However, optimizing the flight paths of multiple UAVs is a significant challenge. The primary concerns include ensuring the UAVs avoid collisions with each other and with obstacles in the flying environment while maintaining efficient end-to-end routes. To address the challenge, this research proposes effective multiple-UAV route planning techniques. Two multiple-UAV approaches based on genetic algorithm (GA) and particle swarm optimization (PSO) are utilized in this paper. In complex scenarios, the proposed methods effectively determine the optimal UAV routes while satisfying various constraints. Simulation results indicate that GA is faster to output final paths but PSO has better flight paths.
References
Aggarwal, Shubhani, Kumar, Neeraj (2020). Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges, Computer communications, 149, 270-299, 2020. https://doi.org/10.1016/j.comcom.2019.10.014
Agiwal, Mamta, Kwon, Hyeyeon, Park, Seungkeun, Jin, Hu (2021). A survey on 4G-5G dual connectivity: Road to 5G implementation, Ieee Access, 9, 16193-16210, 2021. https://doi.org/10.1109/ACCESS.2021.3052462
Ahmed, Shakil, Chowdhury, Mostafa Zaman, Jang, Yeong Min (2020). Energy-efficient UAVto- user scheduling to maximize throughput in wireless networks, IEEE Access, 8, 21215-21225, 2020. https://doi.org/10.1109/ACCESS.2020.2969357
Ahmed, Ramsha, Chen, Yueyun, Hassan, Bilal (2021). Deep learning-driven opportunistic spectrum access (OSA) framework for cognitive 5G and beyond 5G (B5G) networks, Ad Hoc Networks, 123, 102632, 2021. https://doi.org/10.1016/j.adhoc.2021.102632
Bajracharya, Rojeena, Shrestha, Rakesh, Kim, Shiho, Jung, Haejoon (2022). 6G NR-U based wireless infrastructure UAV: Standardization, opportunities, challenges and future scopes, IEEE Access, 10, 30536-30555, 2022. https://doi.org/10.1109/ACCESS.2022.3159698
Bayerlein, Harald, Theile, Mirco, Caccamo, Marco, Gesbert, David (2021). Multi-UAV path planning for wireless data harvesting with deep reinforcement learning, IEEE Open Journal of the Communications Society, 2, 1171-1187, 2021. https://doi.org/10.1109/OJCOMS.2021.3081996
Benzaïd, Chafika and Taleb, Tarik and Farooqi, Muhammad Zubair (2021). Trust in 5G and beyond networks, IEEE Network, 35, 212-222, 2021. https://doi.org/10.1109/MNET.011.2000508
Budhiraja, Ishan, Kumar, Neeraj, Tyagi, Sudhanshu, Tanwar, Sudeep, Han, Zhu, Piran, Md Jalil, Suh, Doug Young (2021). A systematic review on NOMA variants for 5G and beyond, IEEE Access, 9, 85573-85644, 2021. https://doi.org/10.1109/ACCESS.2021.3081601
Chai, Xuzhao, Zheng, Zhishuai, Xiao, Junming, Yan, Li, Qu, Boyang, Wen, Pengwei, Wang, Haoyu, Zhou, You, Sun, Hang (2022). Multi-strategy fusion differential evolution algorithm for UAV path planning in complex environment, Aerospace Science and Technology, 121, 107287, 2022. https://doi.org/10.1016/j.ast.2021.107287
Cheng, Shixin, Zhan, Hao, Yao, Huiqin, Fan, Huayu, Liu, Yan (2021). Large-scale many-objective particle swarm optimizer with fast convergence based on Alpha-stable mutation and Logistic function, Applied Soft Computing, 99, 106947, 2021. https://doi.org/10.1016/j.asoc.2020.106947
Cui, Zhengyang and Wang, Yong (2021). UAV path planning based on multi-layer reinforcement learning technique, Ieee Access, 9, 59486-59497, 2021. https://doi.org/10.1109/ACCESS.2021.3073704
D'Angelo, Gianni, Palmieri, Francesco (2021). GGA: A modified genetic algorithm with gradientbased local search for solving constrained optimization problems, Information Sciences, 547, 136- 162, 2021. https://doi.org/10.1016/j.ins.2020.08.040
Do-Duy, Tan, Nguyen, Long D, Duong, Trung Q, Khosravirad, Saeed R, Claussen, Holger (2021). Joint optimisation of real-time deployment and resource allocation for UAV-aided disaster emergency communications, IEEE Journal on Selected Areas in Communications, 39, 3411-3424, 2021. https://doi.org/10.1109/JSAC.2021.3088662
Feng, Wanmei, Tang, Jie, Yu, Yu, Song, Jingru, Zhao, Nan, Chen, Gaojie, Wong, Kai-Kit, Chambers, Jonathon (2020). UAV-enabled SWIPT in IoT networks for emergency communications, IEEE Wireless Communications, 27, 140-147, 2020. https://doi.org/10.1109/MWC.001.1900656
Sahingoz, Ozgur Koray (2013). Flyable path planning for a multi-UAV system with Genetic Algorithms and Bezier curves, 2013 International Conference on Unmanned Aircraft Systems (ICUAS), 41-48, 2013. https://doi.org/10.1109/ICUAS.2013.6564672
Gu, Zi-Min, Wang, Gai-Ge (2020). Improving NSGA-III algorithms with information feedback models for large-scale many-objective optimization, Future Generation Computer Systems, 107, 49-69, 2020. https://doi.org/10.1016/j.future.2020.01.048
Hajlaoui, Emna, Zaier, Aida, Khlifi, Abdelhakim, Ghodhbane, Jihed, Hamed, Mouna Ben, Sbita, Lassâad (2020). 4G and 5G technologies: A Comparative Study, 2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), 1-6, 2020. https://doi.org/10.1109/ATSIP49331.2020.9231605
Hao, Yunman (2021). Investigation and technological comparison of 4G and 5G networks, Journal of Computer and Communications, 9, 36-43, 2021. https://doi.org/10.4236/jcc.2021.91004
He, Wenjian and Qi, Xiaogang and Liu, Lifang (2021). A novel hybrid particle swarm optimization for multi-UAV cooperate path planning, Applied Intelligence, 51, 7350-7364, 2021. https://doi.org/10.1007/s10489-020-02082-8
Hong, Dooyoung, Lee, Seonhoon, Cho, Young Hoo, Baek, Donkyu, Kim, Jaemin, Chang, Naehyuck (2020). Least-energy path planning with building accurate power consumption model of rotary unmanned aerial vehicle, IEEE Transactions on Vehicular Technology, 69, 14803-14817, 2020. https://doi.org/10.1109/TVT.2020.3040537
Hong, Wei, Jiang, Zhi Hao, Yu, Chao, Hou, Debin, Wang, Haiming, Guo, Chong, Hu, Yun, Kuai, Le, Yu, Yingrui, Jiang, Zhengbo, others (2021). The role of millimeter-wave technologies in 5G/6G wireless communications, IEEE Journal of Microwaves, 1, 101-122, 2021. https://doi.org/10.1109/JMW.2020.3035541
Houssein, Essam H, Gad, Ahmed G, Hussain, Kashif, Suganthan, Ponnuthurai Nagaratnam (2021). Major advances in particle swarm optimization: theory, analysis, and application, Swarm and Evolutionary Computation, 63, 100868, 2021. https://doi.org/10.1016/j.swevo.2021.100868
Huang, Yingqian, Cui, Miao, Zhang, Guangchi, Chen, Wei (2020). Bandwidth, power and trajectory optimization for UAV base station networks with backhaul and user QoS constraints, IEEE Access, 8, 67625-67634, 2020. https://doi.org/10.1109/ACCESS.2020.2986075
Huang, Hailong, Savkin, Andrey V, Ni, Wei (2021). Online UAV trajectory planning for covert video surveillance of mobile targets, IEEE Transactions on Automation Science and Engineering, 19, 735-746, 2021. https://doi.org/10.1109/TASE.2021.3062810
Huang, Hailong, Savkin, Andrey V (2022). Deployment of heterogeneous UAV base stations for optimal quality of coverage, IEEE Internet of Things Journal, 9, 16429-16437, 2022. https://doi.org/10.1109/JIOT.2022.3150292
Jiang, Jia-Jia, Wei, Wen-Xue, Shao, Wan-Lu, Liang, Yu-Feng, Qu, Yuan-Yuan (2021). Research on large-scale bi-level particle swarm optimization algorithm, Ieee Access, 9, 56364-56375, 2021. https://doi.org/10.1109/ACCESS.2021.3072199
Jiang, Xu, Sheng, Min, Nan, ZHAO, Chengwen, XING, Weidang, LU, Xianbin, WANG (2022). Green UAV communications for 6G: A survey, Chinese Journal of Aeronautics, 35, 19-34, 2022. https://doi.org/10.1016/j.cja.2021.04.025
Khorov, Evgeny, Krasilov, Artem, Selnitskiy, Ilya, Akyildiz, Ian F (2020). A framework to maximize the capacity of 5G systems for ultra-reliable low-latency communications, IEEE transactions on mobile computing, 20, 2111-2123, 2020. https://doi.org/10.1109/TMC.2020.2976055
Ladosz, Pawel, Weng, Lilian, Kim, Minwoo, Oh, Hyondong (2022). Exploration in deep reinforcement learning: A survey, Information Fusion, 85, 1-22, 2022. https://doi.org/10.1016/j.inffus.2022.03.003
Lan, Rushi, Zhu, Yu, Lu, Huimin, Liu, Zhenbing, Luo, Xiaonan (2020). A two-phase learningbased swarm optimizer for large-scale optimization, IEEE transactions on cybernetics, 51, 6284- 6293, 2020. https://doi.org/10.1109/TCYB.2020.2968400
Le, Trung-Kien, Salim, Umer, Kaltenberger, Florian (2020). An overview of physical layer design for ultra-reliable low-latency communications in 3GPP releases 15, 16, and 17, IEEE access, 9, 433-444, 2020. https://doi.org/10.1109/ACCESS.2020.3046773
Li, Mushu, Cheng, Nan, Gao, Jie, Wang, Yinlu, Zhao, Lian, Shen, Xuemin (2020). Energyefficient UAV-assisted mobile edge computing: Resource allocation and trajectory optimization, IEEE Transactions on Vehicular Technology, 69, 3424-3438, 2020. https://doi.org/10.1109/TVT.2020.2968343
Lindqvist, Björn and Mansouri, Sina Sharif and Agha-mohammadi, Ali-akbar and Nikolakopoulos, George (2020). Nonlinear MPC for collision avoidance and control of UAVs with dynamic obstacles, IEEE robotics and automation letters, 5, 6001-6008, 2020. https://doi.org/10.1109/LRA.2020.3010730
Marojevic, Vuk, Guvenc, Ismail, Dutta, Rudra, Sichitiu, Mihail L, Floyd, Brian A (2020). Advanced wireless for unmanned aerial systems: 5G standardization, research challenges, and AERPAW architecture, IEEE Vehicular Technology Magazine, 15, 22-30, 2020. https://doi.org/10.1109/MVT.2020.2979494
Qian, Bo, Zhou, Haibo, Ma, Ting, Yu, Kai, Yu, Quan, Shen, Xuemin (2020). Multi-operator spectrum sharing for massive IoT coexisting in 5G/B5G wireless networks, IEEE Journal on Selected Areas in Communications, 39, 881-895, 2020. https://doi.org/10.1109/JSAC.2020.3018803
Rezwan, Sifat, Choi, Wooyeol (2022). Artificial intelligence approaches for UAV navigation: Recent advances and future challenges, IEEE access, 10, 26320-26339, 2022. https://doi.org/10.1109/ACCESS.2022.3157626
Samdanis, Konstantinos, Taleb, Tarik (2020). The road beyond 5G: A vision and insight of the key technologies, IEEE Network, 34, 135-141, 2020. https://doi.org/10.1109/MNET.001.1900228
Schmid, Lukas, Pantic, Michael, Khanna, Raghav, Ott, Lionel, Siegwart, Roland, Nieto, Juan (2020). An efficient sampling-based method for online informative path planning in unknown environments, IEEE Robotics and Automation Letters, 5, 1500-1507, 2020. https://doi.org/10.1109/LRA.2020.2969191
Shafique, Kinza, Khawaja, Bilal A, Sabir, Farah, Qazi, Sameer, Mustaqim, Muhammad (2020). Internet of things (IoT) for next-generation smart systems: A review of current challenges, future trends and prospects for emerging 5G-IoT scenarios, Ieee Access, 8, 23022-23040, 2020. https://doi.org/10.1109/ACCESS.2020.2970118
Shami, Tareq M, El-Saleh, Ayman A, Alswaitti, Mohammed, Al-Tashi, Qasem, Summakieh, Mhd Amen, Mirjalili, Seyedali (2022). Particle swarm optimization: A comprehensive survey, Ieee Access, 10, 10031-10061, 2022. https://doi.org/10.1109/ACCESS.2022.3142859
Siddiqui, Maraj Uddin Ahmed, Qamar, Faizan, Ahmed, Faisal, Nguyen, Quang Ngoc, Hassan, Rosilah (2021). Interference management in 5G and beyond network: Requirements, challenges and future directions, IEEE Access, 9, 68932-68965, 2021. https://doi.org/10.1109/ACCESS.2021.3073543
Soltani, AR, Fernando, T (2004). A fuzzy based multi-objective path planning of construction sites, Automation in construction, 13, 717-734, 2004. https://doi.org/10.1016/j.autcon.2004.04.012
Tahir, Mohammad, Habaebi, Mohamed Hadi, Dabbagh, Mohammad, Mughees, Amna, Ahad, Abdul, Ahmed, Kazi Istiaque (2020). A review on application of blockchain in 5G and beyond networks: Taxonomy, field-trials, challenges and opportunities, IEEE Access, 8, 115876-115904, 2020. https://doi.org/10.1109/ACCESS.2020.3003020
Tran, Dinh-Hieu and Vu, Thang X and Chatzinotas, Symeon and ShahbazPanahi, Shahram and Ottersten, Björn (2020). Coarse trajectory design for energy minimization in UAV-enabled, IEEE Transactions on Vehicular Technology, 69, 9483-9496, 2020. https://doi.org/10.1109/TVT.2020.3001403
Vaezi, Mojtaba, Azari, Amin, Khosravirad, Saeed R, Shirvanimoghaddam, Mahyar, Azari, M Mahdi, Chasaki, Danai, Popovski, Petar (2022). Cellular, wide-area, and non-terrestrial IoT: A survey on 5G advances and the road toward 6G, IEEE Communications Surveys & Tutorials, 24, 1117-1174, 2022. https://doi.org/10.1109/COMST.2022.3151028
Van Huynh, Dang, Do-Duy, Tan, Nguyen, Long D, Le, Minh-Tuan, Vo, Nguyen-Son, Duong, Trung Q (2021). Real-time optimized path planning and energy consumption for data collection in unmanned ariel vehicles-aided intelligent wireless sensing, IEEE Transactions on Industrial Informatics, 18, 2753-2761, 2021. https://doi.org/10.1109/TII.2021.3114358
Wang, Zi-Jia, Zhan, Zhi-Hui, Kwong, Sam, Jin, Hu, Zhang, Jun (2020). Adaptive granularity learning distributed particle swarm optimization for large-scale optimization, IEEE transactions on cybernetics, 51, 1175-1188, 2020. https://doi.org/10.1109/TCYB.2020.2977956
Wang, Feng, Zhang, Heng, Zhou, Aimin (2021). A particle swarm optimization algorithm for mixed-variable optimization problems, Swarm and Evolutionary Computation, 60, 100808, 2021. https://doi.org/10.1016/j.swevo.2020.100808
Xie, Junfei, Carrillo, Luis Rodolfo Garcia, Jin, Lei (2020). Path planning for UAV to cover multiple separated convex polygonal regions, IEEE Access, 8, 51770-51785, 2020. https://doi.org/10.1109/ACCESS.2020.2980203
Xu, Cheng, Xu, Ming, Yin, Chanjuan (2020). Optimized multi-UAV cooperative path planning under the complex confrontation environment, Computer Communications, 162, 196-203, 2020. https://doi.org/10.1016/j.comcom.2020.04.050
Xu, Zhefan, Deng, Di, Shimada, Kenji (2021). Autonomous UAV exploration of dynamic environments via incremental sampling and probabilistic roadmap, IEEE Robotics and Automation Letters, 6, 2729-2736, 2021. https://doi.org/10.1109/LRA.2021.3062008
Yan, Ming and Yuan, Huimin and Xu, Jie and Yu, Ying and Jin, Libiao (2021). Task allocation and route planning of multiple UAVs in a marine environment based on an improved particle swarm optimization algorithm, EURASIP Journal on Advances in Signal Processing, 2021, 1-23, 2021. https://doi.org/10.1186/s13634-021-00804-9
Yao, Huang, Qin, Rongjun, Chen, Xiaoyu (2019). Unmanned aerial vehicle for remote sensing applications-A review, Remote Sensing, 11, 1443, 2019. https://doi.org/10.3390/rs11121443
Yasin, Jawad N, Mohamed, Sherif AS, Haghbayan, Mohammad-Hashem, Heikkonen, Jukka, Tenhunen, Hannu, Plosila, Juha (2020). Unmanned aerial vehicles (uavs): Collision avoidance systems and approaches, IEEE access, 8, 105139-105155, 2020. https://doi.org/10.1109/ACCESS.2020.3000064
Yi, Jiao-Hong, Xing, Li-Ning, Wang, Gai-Ge, Dong, Junyu, Vasilakos, Athanasios V, Alavi, Amir H, Wang, Ling (2020). Behavior of crossover operators in NSGA-III for large-scale optimization problems, Information Sciences, 509, 470-487, 2020. https://doi.org/10.1016/j.ins.2018.10.005
Zhang, Xiao, Duan, Lingjie (2020). Energy-saving deployment algorithms of UAV swarm for sustainable wireless coverage, IEEE Transactions on Vehicular Technology, 69, 10320-10335, 2020. https://doi.org/10.1109/TVT.2020.3004855
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