Raymond Young;Sophia Merrifield;Mark Anderson;Matthew Mazloff;Eric Terrill
{"title":"自主潜水器节能穿越的贪婪深度搜索行为","authors":"Raymond Young;Sophia Merrifield;Mark Anderson;Matthew Mazloff;Eric Terrill","doi":"10.1109/JOE.2024.3429610","DOIUrl":null,"url":null,"abstract":"An energy saving behavior is presented for autonomous underwater vehicles (AUVs) that uses greedy control decisions to take advantage of vertical gradients in ocean currents. The behavior relies on a dynamic vehicle model for motion and power consumption and environmental information that can be realistically obtained and processed onboard. Vehicle model parameters are consistent with a 12.75-in-diameter propeller-driven AUV. Simulation results are presented using a two-year tidally resolving ocean circulation model over three spatially distinct transits in the Southern California Bight. The energy saving behavior is compared to the common practice of transiting at fixed depth, as well as a “best case” scenario in which a vehicle has knowledge of the full-depth ocean current profile at its local position. The proposed behavior saves between 3% and 10% in energy expenditure depending on the vehicle's initial launch depth. On average, it is most efficient to initialize the vehicle at depths corresponding to the base of the surface oceanic mixed layer. Finally, a reduced order approximation of the optimal planning solution shows that the vehicle's depth choices oscillate with dominant tidal constituents for the region.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 4","pages":"1383-1396"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10669820","citationCount":"0","resultStr":"{\"title\":\"A Greedy Depth-Seeking Behavior for Energy-Efficient Transits by an Autonomous Underwater Vehicle\",\"authors\":\"Raymond Young;Sophia Merrifield;Mark Anderson;Matthew Mazloff;Eric Terrill\",\"doi\":\"10.1109/JOE.2024.3429610\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An energy saving behavior is presented for autonomous underwater vehicles (AUVs) that uses greedy control decisions to take advantage of vertical gradients in ocean currents. The behavior relies on a dynamic vehicle model for motion and power consumption and environmental information that can be realistically obtained and processed onboard. Vehicle model parameters are consistent with a 12.75-in-diameter propeller-driven AUV. Simulation results are presented using a two-year tidally resolving ocean circulation model over three spatially distinct transits in the Southern California Bight. The energy saving behavior is compared to the common practice of transiting at fixed depth, as well as a “best case” scenario in which a vehicle has knowledge of the full-depth ocean current profile at its local position. The proposed behavior saves between 3% and 10% in energy expenditure depending on the vehicle's initial launch depth. On average, it is most efficient to initialize the vehicle at depths corresponding to the base of the surface oceanic mixed layer. Finally, a reduced order approximation of the optimal planning solution shows that the vehicle's depth choices oscillate with dominant tidal constituents for the region.\",\"PeriodicalId\":13191,\"journal\":{\"name\":\"IEEE Journal of Oceanic Engineering\",\"volume\":\"49 4\",\"pages\":\"1383-1396\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10669820\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Oceanic Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10669820/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Oceanic Engineering","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10669820/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
A Greedy Depth-Seeking Behavior for Energy-Efficient Transits by an Autonomous Underwater Vehicle
An energy saving behavior is presented for autonomous underwater vehicles (AUVs) that uses greedy control decisions to take advantage of vertical gradients in ocean currents. The behavior relies on a dynamic vehicle model for motion and power consumption and environmental information that can be realistically obtained and processed onboard. Vehicle model parameters are consistent with a 12.75-in-diameter propeller-driven AUV. Simulation results are presented using a two-year tidally resolving ocean circulation model over three spatially distinct transits in the Southern California Bight. The energy saving behavior is compared to the common practice of transiting at fixed depth, as well as a “best case” scenario in which a vehicle has knowledge of the full-depth ocean current profile at its local position. The proposed behavior saves between 3% and 10% in energy expenditure depending on the vehicle's initial launch depth. On average, it is most efficient to initialize the vehicle at depths corresponding to the base of the surface oceanic mixed layer. Finally, a reduced order approximation of the optimal planning solution shows that the vehicle's depth choices oscillate with dominant tidal constituents for the region.
期刊介绍:
The IEEE Journal of Oceanic Engineering (ISSN 0364-9059) is the online-only quarterly publication of the IEEE Oceanic Engineering Society (IEEE OES). The scope of the Journal is the field of interest of the IEEE OES, which encompasses all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.