Research on Cooperative Transportation of Underwater Payload Based on Cooperative Formation Control of Multiple Unmanned Underwater Vehicles

doi:10.3901/JME.2025.24.363

Abstract

Abstract: Aiming at the application scenario of underwater object transportation in a multi-obstacle environment, the formation reconfiguration and trajectory planning issues during the cooperative transportation and point-to-point delivery of underwater object by multiple unmanned underwater vehicles(UUVs) are explored. A formation control and motion planner for the multi-UUV cooperative transportation system is designed. Firstly, to meet the formation control requirements of multi-UUV cooperative transportation, a formation controller for the multi-UUV system is designed based on rigid graph theory, affine transformation, and backstepping control theory. The core function of this controller is to control the multi-UUV system to form a specific formation configuration, thereby steadily lifting and transporting underwater object. During transportation, the system can reconfigure the shape of the formation using affine transformation according to different obstacle environment information or specific task requirements. The stability of the closed-loop formation control system is analyzed using Lyapunov function, which verifies the reliability of the control scheme. Secondly, to address the trajectory planning challenges of multi-UUV cooperative transportation in complex multi-obstacle environments, a collision-free trajectory planning algorithm suitable for multi-UUV formations is designed based on the fluid disturbance strategy, ensuring that the formation can safely avoid obstacles in complex environments. Finally, the effectiveness of the proposed algorithm is verified using Matlab simulations. The simulation results show that the UUVs in the formation can quickly form and stably maintain the desired transportation formation, and can flexibly maneuver along the planned trajectory to avoid obstacles. Ultimately, the goal of collaborative transportation of large underwater object by multiple UUVs is achieved.

Key words: multi-unmanned underwater vehicle, formation control, underwater cooperative transportation, motion planning

CLC Number:

TP242

PANG Wen, ZHU Daqi, LIN Shuhan, CHEN Mingzhi. Research on Cooperative Transportation of Underwater Payload Based on Cooperative Formation Control of Multiple Unmanned Underwater Vehicles[J]. Journal of Mechanical Engineering, 2025, 61(24): 363-376.

References

[1] 朱大奇,庞文,任科蒙. 多AUV水下协作搜索研究现状与展望[J]. 上海理工大学学报,2022,44(5):417-428. ZHU Daqi,PANG Wen,REN Kemeng. Research status and prospect of multi-autonomous underwater vehicle cooperative search control[J]. Journal of University of Shanghai for Science and Technology,2022,44(5):417-428.
[2] WANG Q,FAN S,ZHANG Y,et al. A novel adaptive sliding observation-based cooperative positioning algorithm under factor graph framework for multiple UUVs[J]. IEEE Transactions on Industrial Informatics,2023,19(8):8743-8753.
[3] 殷虎,石磊鑫. 多UUV集群协同作业技术研究现状及发展趋势分析[J]. 舰船电子工程,2024,44(2):4-9. YIN Hu,SHI Leixin. Research status and development trend of multi-UUV cluster collaborative work technology[J]. Ship Electronic Engineering,2024,44(2):4-9.
[5] 严浙平,刘祥玲. 多UUV协调控制技术研究现状及发展趋势[J]. 水下无人系统学报,2019,27(3):226-231. YAN Zheping,LIU Xiangling. Research status and development trend of multi-UUV coordinated control technology:A review[J]. Journal of Unmanned Undersea Systems,2019,27(3):226-231.
[5] HESHMATI-ALAMDARI S,KARRAS G,KYRIAKOPOULOS K. A predictive control approach for cooperative transportation by multiple underwater vehicle manipulator systems[J]. IEEE Transactions on Control Systems Technology,2022,30(3):917-930.
[6] SIMETTI E,CASALINO G. Manipulation and transportation with cooperative underwater vehicle manipulator systems[J]. IEEE Journal of Oceanic Engineering,2017,42(4):782-799.
[7] 宋子扬. 水下应急封井装置陆地组装测试及海上运输方案[J]. 石油知识,2023(1):52-53. SONG Ziyang. Onshore assembly test and Marine transportation scheme of subsea capping device[J]. Technical Equipment,2023(1):52-53.
[8] 刘云平,蒋长胜,张婷婷,等. 考虑内部避碰的多无人机有限时间环形编队控制[J]. 机械工程学报,2022,58(1):61-68. LIU Yunping,JIANG Changsheng,ZHANG Tingting,et al. Multi-UAV finite-time ring formation control considering internal collision avoidance[J]. Journal of Mechanical Engineering,2022,58(1):61-68.
[9] 李娟,袁锐锟,张宏瀚. 基于领航跟随法的多AUV编队控制算法研究[J]. 仪器仪表学报,2019,40(6):237-246. LI Juan,YUAN Ruikun,ZHANG Honghan. Research on multiple AUVs formation control algorithm based on leader-follower method[J]. Chinese Journal of Scientific Instrument,2019,40(6):237-246.
[10] WEN J,YANG J,LI Y,et al. Behavior-based formation control digital twin for multi-AUG in edge computing[J]. IEEE Transactions on Network Science and Engineering,2023,10(5):2791-2801.
[11] 崔立堃,冯绪永,王承祥. 人工势场和虚拟结构结合的无人车编队及避障研究[J]. 兵器装备工程学报,2022,43(9):304-308. CUI Liku,FENG Xuyong,WANG Chengxiang. Research of unmanned vehicle formation and obstacle avoidance combining artificial potential field and virtual structure[J]. Journal of Ordnance Equipment Engineering,2022,43(9):304-308.
[12] 张宇宸,段海滨,魏晨. 基于深度强化学习的无人机集群数字孪生编队避障[J]. 工程科学学报,2024,46(7):1187-1196. ZHANG Yuchen,DUAN Haibin,WEI Chen. Digital twin-based obstacle avoidance method for unmanned aerial vehicle formation control using deep reinforcement learning[J]. Chinese Journal of Engineering,2024,46(7):1187-1196.
[13] 武星,余文康,楼佩煌,等. 大型部件的多机器人合作搬运协同导引控制[J]. 中国机械工程,2022,33(13):1586-1595. WU Xing,YU Wenkang,LOU Peihuang,et al. Coordinated guidance control for multi-robot cooperative transportation of large-sized objects[J]. China Mechanical Engineering,2022,33(13):1586-1595.
[14] 张海森,张煌,王常顺. 基于多机器人编队控制的大件物品协同搬运[J]. 山东大学学报(工学版),2023,53(4):157-162. ZHANG Haisen,ZHANG Huang,WANG Changshun. Collaborative transportation for bulky items based on multi-robot formation contrl[J]. Journal of Shandong University (Engineering Science),2023,53(4):157-162.
[15] LI W. Notion of control-law module and modular framework of cooperative transportation using multiple nonholonomic robotic agents with physical rigid-formation-motion constraints[J]. IEEE Transactions on Cybernetics,2016,46(5):1242-1248.
[16] 刘亚,黄攀峰,张帆. 多无人机绳索悬挂协同搬运固定时间控制[J]. 导航定位与授时,2021,8(1):21-30. LIU Ya,HUANG Panfeng,ZHANG Fan. Fixed-time control of cooperative transportation of payloads by tethers from multiple UAVs[J]. Navigation Positioning & Timing,2021,8(1):21-30.
[17] 曹洁,朱宁宁. 动态环境中的多机器人协同搬运[J]. 计算机工程与应用,2013,49(23):252-256. CAO Jie,ZHU Ningning. Multi-robot cooperative carrying in dynamic environment[J]. Computer Engineering and Applications,2013,49(23):252-256.
[18] ZHANG X,ZHANG F,HUANG P. Formation planning for tethered multirotor UAV cooperative transportation with unknown payload and cable length[J]. IEEE Transactions on Automation Science and Engineering,2024,21(3):3449-3460.
[19] PANG W,ZHU D,SUN C. Multi-AUV Formation reconfiguration obstacle avoidance algorithm based on affine transformation and improved artificial potential field under ocean currents disturbance[J]. IEEE Transactions on Automation Science and Engineering,2024,21(2):1469-1487.
[20] PANG W,ZHU D,CHU Z,et al. Distributed adaptive formation reconfiguration control for multiple AUVs based on affine transformation in three-dimensional ocean environments[J]. IEEE Transactions on Vehicular Technology,2023,72(6):7338-7350.
[21] PANG W,ZHU D,LIU C,et al. The multi-AUV time-varying formation reconfiguration control based on rigid-graph theory and affine transformation[J]. Ocean Engineering,2023,270:113521.
[22] 庄红超,王柠,董凯伦,等. 非完整约束大负重比六足机器人多机动态协同编队避障控制策略[J]. 机械工程学报,2024,60(1):284-295. ZHANG Hongchao,WANG Ning,DONG Kailun,et al. Obstacle avoidance control strategy of multi-robot dynamic cooperative formation of large-load-ratio six-legged robot under nonholonomic constraints[J]. Journal of Mechanical Engineering,2024,60(1):284-295.
[23] WU J,WANG H,LI N,et al. Formation obstacle avoidance:A fluid-based solution[J]. IEEE Systems Journal,2020,14(1):1479-1490.
[24] DO K D,PAN J. Control of ships and underwater vehicles:Design for underactuated and nonlinear marine systems[M]. London:Springer,2009.
[25] WANG H,LYU W,YAO P,et al. Three-dimensional path planning for unmanned aerial vehicle based on interfered fluid dynamical system[J]. Chinese Journal of Aeronautics,2015,28(1):229-239.
[26] RAMAZANI S,SELMIC R,QUEIROZ M. Rigidity-based multiagent layered formation control[J]. IEEE Transactions on Cybernetics,2017,47(8):1902-1913.

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