Xuejian Bai;Yu Wang;Zixuan Yang;Jiaqi Lv;Xiaolong Hui;Shuo Wang;Min Tan
{"title":"Design and Pipeline Tracking Control of an Underwater Biomimetic Vehicle-Manipulator System With Hybrid Propulsion","authors":"Xuejian Bai;Yu Wang;Zixuan Yang;Jiaqi Lv;Xiaolong Hui;Shuo Wang;Min Tan","doi":"10.1109/TCYB.2025.3568390","DOIUrl":null,"url":null,"abstract":"Underwater vehicle-manipulator systems (UVMSs) play crucial roles in the fields of underwater target monitoring and pipeline maintenance. However, achieving accurate tracking for underwater pipelines is challenging due to the complexity of UVMSs in terms of nonlinearity, strong coupling and underactuation. To solve the aforementioned problems, an underwater biomimetic vehicle-manipulator system (UBVMS) and an underwater pipeline tracking control method based on the robot vision are proposed. The UBVMS is equipped with the biomimetic undulatory fin propulsors and the biomimetic flipper propulsors, which are inspired by the median and/or paired fin propulsion mode and the body and/or caudal fin propulsion mode of fishes, respectively. The biomimetic undulatory fin propulsors provide the UBVMS with advantages of maneuverability and stability, while the biomimetic flipper propulsors enable the UBVMS to have improved acceleration ability. A tracking control algorithm with adaptive weight coefficients is designed to improve the pose stability of the UBVMS. A fuzzy rule mapping model is constructed to describe the nonlinear relationship between the biomimetic propulsors’ control parameters and the propulsive force/torque. Finally, four types of pipeline tracking experiments are conducted to verify the effectiveness and feasibility of the proposed UBVMS and control algorithm.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 7","pages":"3073-3084"},"PeriodicalIF":10.5000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cybernetics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11016812/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Underwater vehicle-manipulator systems (UVMSs) play crucial roles in the fields of underwater target monitoring and pipeline maintenance. However, achieving accurate tracking for underwater pipelines is challenging due to the complexity of UVMSs in terms of nonlinearity, strong coupling and underactuation. To solve the aforementioned problems, an underwater biomimetic vehicle-manipulator system (UBVMS) and an underwater pipeline tracking control method based on the robot vision are proposed. The UBVMS is equipped with the biomimetic undulatory fin propulsors and the biomimetic flipper propulsors, which are inspired by the median and/or paired fin propulsion mode and the body and/or caudal fin propulsion mode of fishes, respectively. The biomimetic undulatory fin propulsors provide the UBVMS with advantages of maneuverability and stability, while the biomimetic flipper propulsors enable the UBVMS to have improved acceleration ability. A tracking control algorithm with adaptive weight coefficients is designed to improve the pose stability of the UBVMS. A fuzzy rule mapping model is constructed to describe the nonlinear relationship between the biomimetic propulsors’ control parameters and the propulsive force/torque. Finally, four types of pipeline tracking experiments are conducted to verify the effectiveness and feasibility of the proposed UBVMS and control algorithm.
期刊介绍:
The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.