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A warm-started trajectory planner for fixed-wing unmanned aerial vehicle formation. (English) Zbl 1525.93289


MSC:

93C85 Automated systems (robots, etc.) in control theory
93B51 Design techniques (robust design, computer-aided design, etc.)
90B06 Transportation, logistics and supply chain management
93C95 Application models in control theory

Software:

CasADi; Ipopt
Full Text: DOI

References:

[1] Guerriero, F.; Surace, R.; Loscrí, V.; Natalizio, E., A multi-objective approach for unmanned aerial vehicle routing problem with soft time windows constraints, Appl. Math. Model., 38, 3, 839-852 (2014) · Zbl 1427.90045
[2] Gonzélez, D.; Pérez, J.; Milanés, V.; Nashashibi, F., A review of motion planning techniques for automated vehicles, IEEE Trans. Intell. Transp. Syst., 17, 4, 1135-1145 (2016)
[3] Zhang, S.; Zhang, H.; Di, B.; Song, L., Cellular UAV-to-X communications: design and optimization for multi-UAV networks, IEEE Trans. Wireless Commun., 18, 2, 1346-1359 (2019)
[4] Yu, X.; Gao, X.; Wang, L.; Wang, X.; Ding, Y.; Lu, C.; Zhang, S., Cooperative multi-uav task assignment in cross-regional joint operations considering ammunition inventory, Drones, 6, 3 (2022)
[5] Ángel Madridano; Al-Kaff, A.; Martín, D.; de la Escalera, A., Trajectory planning for multi-robot systems: methods and applications, Expert Syst. Appl., 173, 114660 (2021)
[6] Fu, X.; Huang, J.; Jing, Z., Complex switching dynamics and chatter alarm for aerial agents with artificial potential field method, Appl. Math. Model., 107, 637-649 (2022) · Zbl 1503.34048
[7] Gao, X.; Wang, L.; Yu, X.; Su, X.; Ding, Y.; Lu, C.; Peng, H.; Wang, X., Conditional probability based multi-objective cooperative task assignment for heterogeneous UAVs, Eng. Appl. Artif. Intell., 106404 (2023)
[8] Shanmugavel, M.; Tsourdos, A.; White, B.; Żbikowski, R., Co-operative path planning of multiple UAVs using dubins paths with clothoid arcs, Control Eng. Pract., 18, 9, 1084-1092 (2010)
[9] Qiao, H.; Chen, J.; Huang, X., A survey of brain-inspired intelligent robots: integration of vision, decision, motion control, and musculoskeletal systems, IEEE Trans. Cybern., 52, 10, 11267-11280 (2022)
[10] Zhu, J.-W.; Gu, C.-Y.; Ding, S. X.; Zhang, W.-A.; Wang, X.; Yu, L., A new observer-based cooperative fault-tolerant tracking control method with application to networked multiaxis motion control system, IEEE Trans. Ind. Electron., 68, 8, 7422-7432 (2021)
[11] Ren, W.; Beard, R., Trajectory tracking for unmanned air vehicles with velocity and heading rate constraints, IEEE Trans. Control Syst. Technol., 12, 5, 706-716 (2004)
[12] Arifianto, O.; Farhood, M., Optimal control of a small fixed-wing UAV about concatenated trajectories, Control Eng. Pract., 40, 113-132 (2015)
[13] Aggarwal, S.; Kumar, N., Path planning techniques for unmanned aerial vehicles: a review, solutions, and challenges, Comput. Commun., 149, 270-299 (2020)
[14] Kim, S.-H.; Padilla, G. E.G.; Kim, K.-J.; Yu, K.-H., Flight path planning for a solar powered UAV in wind fields using direct collocation, IEEE Trans. Aerosp. Electron. Syst., 56, 2, 1094-1105 (2020)
[15] Peng, H.; Bao, J.; Huang, G.; Li, Z.; Wang, X., Chance-constrained sneaking trajectory planning for reconnaissance robots, Appl. Math. Model., 112, 224-237 (2022) · Zbl 1505.93167
[16] Zhao, Y.; Zheng, Z.; Liu, Y., Survey on computational-intelligence-based UAV path planning, Knowl. Based Syst., 158, 54-64 (2018)
[17] Paden, B.; Čáp, M.; Yong, S. Z.; Yershov, D.; Frazzoli, E., A survey of motion planning and control techniques for self-driving urban vehicles, IEEE Trans. Intell. Veh., 1, 1, 33-55 (2016)
[18] Sedighi, S.; Nguyen, D.-V.; Kuhnert, K.-D., Guided hybrid A-star path planning algorithm for valet parking applications, Proceedings of 5th International Conference on Control, Automation and Robotics (ICCAR), 570-575 (2019)
[19] Wang, X.; Roy, S.; Farí, S.; Baldi, S., Adaptive vector field guidance without a priori knowledge of course dynamics and wind, IEEE/ASME Trans. Mechatron., 27, 6, 4597-4607 (2022)
[20] Farí, S.; Wang, X.; Roy, S.; Baldi, S., Addressing unmodeled path-following dynamics via adaptive vector field: a uav test case, IEEE Trans. Aerosp. Electron. Syst., 56, 2, 1613-1622 (2020)
[21] Huang, Y.; Ding, H.; Zhang, Y.; Wang, H.; Cao, D.; Xu, N.; Hu, C., A motion planning and tracking framework for autonomous vehicles based on artificial potential field elaborated resistance network approach, IEEE Trans. Ind. Electron., 67, 2, 1376-1386 (2020)
[22] Fan, J.; Chen, X.; Liang, X., UAV Trajectory planning based on bi-directional APF-RRT* algorithm with goal-biased, Expert Syst. Appl., 213, 119137 (2022)
[23] Pan, Z.; Zhang, C.; Xia, Y.; Xiong, H.; Shao, X., An improved artificial potential field method for path planning and formation control of the multi-UAV systems, IEEE Trans. Circuits Syst. II: Express Briefs, 69, 3, 1129-1133 (2022)
[24] Aradi, S., Survey of deep reinforcement learning for motion planning of autonomous vehicles, IEEE Trans. Intell. Transp. Syst., 23, 2, 740-759 (2022)
[25] Mahdavi, S.; Shiri, M. E.; Rahnamayan, S., Metaheuristics in large-scale global continues optimization: a survey, Inf. Sci. (Ny), 295, 407-428 (2015)
[26] Roberge, V.; Tarbouchi, M.; Labonté, G., Fast genetic algorithm path planner for fixed-wing military UAV using GPU, IEEE Trans. Aerosp Electron. Syst., 54, 5, 2105-2117 (2018)
[27] Shao, S.; Peng, Y.; He, C.; Du, Y., Efficient path planning for UAV formation via comprehensively improved particle swarm optimization, ISA Trans., 97, 415-430 (2020)
[28] Li, B.; Zhang, J.; Dai, L.; Teo, K. L.; Wang, S., A hybrid offline optimization method for reconfiguration of multi-UAV formations, IEEE Trans. Aerosp. Electron. Syst., 57, 1, 506-520 (2021)
[29] Teng, J.; An, Y.; Wang, L., Time-optimal control problem for a linear parameter varying system with nonlinear item, J. Franklin Inst., 359, 2, 859-869 (2022) · Zbl 1481.93048
[30] Chai, R.; Tsourdos, A.; Savvaris, A.; Xia, Y.; Chai, S., Real-time reentry trajectory planning of hypersonic vehicles: a two-step strategy incorporating fuzzy multiobjective transcription and deep neural network, IEEE Trans. Ind. Electron., 67, 8, 6904-6915 (2020)
[31] Egerstedt, M.; Martin, C. F., Optimal trajectory planning and smoothing splines, Automatica, 37, 7, 1057-1064 (2001) · Zbl 0989.93038
[32] Liu, G.; Li, B.; Ji, Y., A modified HP-adaptive pseudospectral method for multi-UAV formation reconfiguration, ISA Trans., 129, 217-229 (2022)
[33] Zhang, Z.; Li, J.; Wang, J., Sequential convex programming for nonlinear optimal control problems in UAV path planning, Aerosp. Sci. Technol., 76, 280-290 (2018)
[34] Wang, Z.; Liu, L.; Long, T.; Xu, G., Efficient unmanned aerial vehicle formation rendezvous trajectory planning using dubins path and sequential convex programming, Eng. Optim., 51, 8, 1412-1429 (2019)
[35] Wang, J.; Xin, M., Integrated optimal formation control of multiple unmanned aerial vehicles, IEEE Trans. Control Syst. Technol., 21, 5, 1731-1744 (2013)
[36] Rachman, D. M.; Maki, A.; Miyauchi, Y.; Umeda, N., Warm-started semionline trajectory planner for ships automatic docking (berthing), Ocean Eng., 252, 111127 (2022)
[37] Guo, H.; Shen, C.; Zhang, H.; Chen, H.; Jia, R., Simultaneous trajectory planning and tracking using an MPC method for cyber-physical systems: a case study of obstacle avoidance for an intelligent vehicle, IEEE Trans. Ind. Inf., 14, 9, 4273-4283 (2018)
[38] Wang, X.; Li, B.; Su, X.; Peng, H.; Wang, L.; Lu, C.; Wang, C., Autonomous dispatch trajectory planning on flight deck: a search-resampling-optimization framework, Eng. Appl. Artif. Intell., 119, 105792 (2023)
[39] Wang, X.; Deng, Z.; Peng, H.; Wang, L.; Wang, Y.; Tao, L.; Lu, C.; Peng, Z., Autonomous docking trajectory optimization for unmanned surface vehicle: a hierarchical method, Ocean Eng., 279, 114156 (2023)
[40] Kim, H.; Kim, Y., Trajectory optimization for unmanned aerial vehicle formation reconfiguration, Eng. Optim., 46, 1, 84-106 (2014)
[41] Khatib, O., The Potential Field Approach And Operational Space Formulation In Robot Control, 367-377 (1986), Springer US: Springer US Boston, MA
[42] Wang, X.; Liu, J.; Peng, H.; Qie, X.; Zhao, X.; Lu, C., A simultaneous planning and control method integrating APF and MPC to solve autonomous navigation for USVs in unknown environments, J. Intell. Rob. Syst., 105, 2, 1-16 (2022)
[43] Chetverikov, D.; Svirko, D.; Stepanov, D.; Krsek, P., The trimmed iterative closest point algorithm, International Conference on Pattern Recognition, volume 3, 545-548 (2002)
[44] Liu, X.; Frank, J., Symplectic runge-kutta discretization of a regularized forward-backward sweep iteration for optimal control problems, J. Comput. Appl. Math., 383, 113133 (2021) · Zbl 1447.49043
[45] Andersson, J. A.E.; Gillis, J.; Rawlings, G. H.J. B.; Diehl, M., Casadi – a software framework for nonlinear optimizationand optimal control, Math. Program. Comput., 11, 1, 1-36 (2019) · Zbl 1411.90004
[46] Wächter, A.; Biegler, L. T., On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Math. Program., 106, 1, 25-57 (2006) · Zbl 1134.90542
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