Wen Pang, Daqi Zhu, and Simon X. Yang


  1. [1] B.K. Sahu and B. Subudhi, Flocking control ofmultiple AUVs based on fuzzy potential functions,IEEE Transactions on Fuzzy Systems, 26(5), 2018,2539–2551.
  2. [2] D. Zhu, H. Huang, and S.X. Yang, Dynamic task assignmentand path planning of multi-AUV system based on an improvedself-organizing map and velocity synthesis method in three-dimensional underwater workspace, IEEE Transactions onCybernetics, 43(2), 2013, 504–514.
  3. [3] C. Yuan, S. Licht, and H. He, Formation learning controlof multiple autonomous underwater vehicles with heteroge-neous nonlinear uncertain dynamics, IEEE Transactions onCybernetics, 48(10), 2018, 2920–2934.
  4. [4] T. Matsuda, T. Maki, Y. Sato, and T. Sakamaki, Experimentalevaluation of accuracy and efficiency of alternating landmarknavigation by multiple AUVs, IEEE Journal of OceanicEngineering, 43(2), 2018, 288–310.
  5. [5] Q. Zhang, J. Zhang, A. Chemori, and X. Xiang, Virtual sub-merged floating operational system for robotic manipulation,Complexity, 2018, 2018, 1–18.
  6. [6] Z. Wang, S. Yang, X. Xiang, A. Vasilijevi´c, N. Miˇskovi´c, andD. Na, Cloud-based mission control of USV fleet: Architec-ture, implementation and experiments, Control EngineeringPractice, 106, 2021, 104657.
  7. [7] J. Wang, C. Wang, Y. Wei, and C. Zhang, Observer-based neural formation control of leader–follower AUVswith input saturation, IEEE Systems Journal, 15(2), 2021,2553–2561.
  8. [8] L. Ma, Cooperative target tracking in balanced circularformation with time-varying radius, International Journal ofRobotics and Automation, 35(4), 2020, 86–100.
  9. [9] T. Soleymani and F. Saghafi, Behavior-based accelerationcommanded formation flight control, Proc. Int. Conf. onControl, Automation and Systems (ICCAS), Gyeonggi-do,2010, 1340–1345.
  10. [10] X. Li and D. Zhu, An adaptive SOM neural networkmethod for distributed formation control of a group of AUVs,IEEE Transactions on Industrial Electronics, 65(10), 2018,8260–8270.205
  11. [11] H. Du, W. Zhu, G. Wen, Z. Duan, and J. L¨u, Distributedformation control of multiple quadrotor aircraft based onnonsmooth consensus algorithms, IEEE Transactions onCybernetics, 49(1), 2019, 342–353.
  12. [12] Y. Liu, P. Huang, F. Zhang, and Y. Zhao, Distributedformation control using artificial potentials and neural networkfor constrained multiagent systems, IEEE Transactions onControl Systems Technology, 28(2), 2020, 697–704.
  13. [13] B. Hadi, A. Khosravi, and P. Sarhadi, A review of thepath planning and formation control for multiple autonomousunderwater vehicles, Journal of Intelligent & Robotic Systems,101, 67, 2021.
  14. [14] C. Cheng, Q. Sha, B. He, and G. Li, Path planning andobstacle avoidance for AUV: A review, Ocean Engineering,235(1), 2021, 109355.
  15. [15] J. Wen, J. Yang, and T. Wang, Path planning forautonomous underwater vehicles under the influence ofocean currents based on a fusion heuristic algorithm,IEEE Transactions on Vehicular Technology, 70(9), 2021,8529–8544.
  16. [16] M. Alajlan, I. Chaari, A. Koubaa, H. Bennaceur, A. Ammar,and H. Youssef, Global robot path planning using GA forlarge grid maps: Modelling, performance and experimentation,International Journal of Robotics and Automation, 31(6), 2016,1–12.
  17. [17] G. Wen, C.L.P. Chen, and Y.-J. Liu, Formation control withobstacle avoidance for a class of stochastic multiagent systems,IEEE Transactions on Industrial Electronics, 65(7), 2018,5847–5855.
  18. [18] H. Xiao, Z. Li, and C.L.P. Chen, Formation control of leader–follower mobile robots’ systems using model predictive controlbased on neural-dynamic optimization, IEEE Transactions onIndustrial Electronics, 63(9), 2016, 5752–5762.
  19. [19] C. Bai, P. Yan, W. Pan, and J. Guo, Learning-basedmulti-robot formation control with obstacle avoidance, IEEETransactions on Intelligent Transportation Systems, 23(8),2022, 11811–11822.
  20. [20] J. Wu, H. Wang, N. Li, and Z. Su, Formation obstacle avoidance:A fluid-based solution, IEEE Systems Journal, 14(1), 2020,1479–1490.
  21. [21] W. Huang, H. Fang, and L. Li, Obstacle avoiding policy ofmulti-AUV formation based on virtual AUV, Proc. 6th Int.Conf. on Fuzzy Systems and Knowledge Discovery, Tianjin,2009, 131–135.
  22. [22] C. Xiang, H. Sun, and X. Xu, A novel cooperativehunting algorithm for multi-AUV in underwater environments,International Journal of Robotics and Automation, 35(6), 2020,425–435.
  23. [23] R.S. McEwen, S.P. Rock, and B. Hobson, Iceberg wallfollowing and obstacle avoidance by an AUV, Proc. IEEE/OESAutonomous Underwater Vehicle Workshop (AUV), Porto,2018, 1–8.
  24. [24] K. Wu and P. Yao, Obstacle avoidance for AUV by Q-learningbased guidance vector field, Proc. 3rd Int. Conf. on UnmannedSystems (ICUS), Harbin, 2020, 702–707.
  25. [25] G. Xiang and X. Xiang, 3D trajectory optimizationof the slender body freely falling through water usingcuckoo search algorithm, Ocean Engineering, 235(1), 2021,109354.
  26. [26] X. Yu, W.-N. Chen, T. Gu, H. Yuan, H. Zhang, and J.Zhang, ACO-A: Ant colony optimization plus A for 3-D traveling in environments with dense obstacles, IEEETransactions on Evolutionary Computation, 23(4), 2019,617–631.
  27. [27] K. Shojaei, Neural network formation control of underactuatedautonomous underwater vehicles with saturating actuators,Neurocomputing, 194, 2016, 372–384.
  28. [28] G. Xia, Y. Zhang, W. Zhang, X. Chen, and H. Yang, Dualclosed-loop robust adaptive fast integral terminal sliding modeformation finite-time control for multi-underactuated AUVsystem in three dimensional space, Ocean Engineering, 233,2021, 108903.
  29. [29] Y.-L. Chen, X.-W. Ma, G.-Q. Bai, Y. Sha, and J. Liu,Multi-autonomous underwater vehicle formation control andcluster search using a fusion control strategy at complexunderwater environment, Ocean Engineering, 216(7), 2020,108048.
  30. [30] J.-H. Li, D. Park, H. Kang, and G.R. Cho, 3D formationcontrol of multiple torpedo-type underactuated AUVs, Proc.21st IFAC, Berlin, 2020, 14680–14685.
  31. [31] G. Han, X. Qi, Y. Peng, C. Lin, Y. Zhang, and Q. Lu,Early warning obstacle avoidance-enabled path planning formulti-AUV-based maritime transportation systems, IEEETransactions on Intelligent Transportation Systems, 24(2),2023, 2656–2667.
  32. [32] X. Yang, W. Wang, and P. Huang, Distributed optimalconsensus with obstacle avoidance algorithm of mixed-orderUAVs–USVs–UUVs systems, ISA Transactions, 107, 2020,270–286.
  33. [33] X. Yu, W.-N. Chen, X.-M. Hu, T. Gu, H. Yuan, Y. Zhou, andJ. Zhang, Path planning in multiple-AUV systems for difficulttarget traveling missions: A hybrid metaheuristic approach,IEEE Transactions on Cognitive and Developmental Systems,12(3), 2020, 561–574.
  34. [34] J. Zhang, J. Sha, G. Han, J. Liu, and Y. Qian, A cooperative-control-based underwater target escorting mechanism withmultiple autonomous underwater vehicles for underwaterInternet of Things, IEEE Internet of Things Journal, 8(6),2021, 4403–441.
  35. [35] G. Ding, D. Zhu, and B. Sun, Formation control and obstacleavoidance of multi-AUV for 3-D underwater environment, Proc.33rd Chinese Control Conf., Nanjing, 2014, 8347–8352.
  36. [36] B.D.O. Anderson, C. Yu, B. Fidan, and J.M. Hendrickx, Rigidgraph control architectures for autonomous formations, IEEEControl Systems Magazine, 28(6), 2008, 48–63.
  37. [37] Y. Guo, X. Liu, W. Zhang, X. Liu, and Y. Yang, Obstacleavoidance planning for quadrotor UAV based on improvedadaptive artificial potential field, Proc. Chinese AutomationCongress (CAC), Hangzhou,2019, 2598–2603.
  38. [38] P.K. Biswal and S. Banerjee, A parallel approach for affinetransform of 3D biomedical images, Proc. Int.Conf. onElectronics and Information Engineering, Kyoto, Aug. 2010,V1-329–V1-332.
  39. [39] S. Ramazani, R. Selmic, and M. de Queiroz, Rigidity-basedmultiagent layered formation control, IEEE Transactions onCybernetics, 47(8), 2017, 1902–1913.
  40. [40] P. Zhang, M. de Queiroz, and X. Cai, Three-dimensionaldynamic formation control of multi-agent systems using rigidgraphs, Journal of Dynamic Systems, Measurement, andControl, 137(11), 2015, 111006.
  41. [41] H.K. Khalil, Nonlinear Systems, 3rd ed. (Englewood Cliffs,NJ: Prentice-Hall, 2002).

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