Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603820
Hongmei Zhang, Jianhu Zhao, Baohua Xu
In order to improve the accuracy of underwater topographic measurement, the method for the precise determination of instantaneous height of transducer is studied. The software, which is used for implementing the blend of GPS height and heave so as to accurately present instantaneous height of transducer, is developed. The software structure design, key techniques and main function modules including quality control, time synchronization, attitude correction, as well as signal extraction and blend are depicted in detail. Moreover, the software is tested and applied in the actual experiments. The results show that the accuracy and performance of the software are high and can satisfy the actual application.
{"title":"Software development for the determination of instantaneous height of transducer based on the blend of GPS height and heave","authors":"Hongmei Zhang, Jianhu Zhao, Baohua Xu","doi":"10.1109/OCEANSSYD.2010.5603820","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603820","url":null,"abstract":"In order to improve the accuracy of underwater topographic measurement, the method for the precise determination of instantaneous height of transducer is studied. The software, which is used for implementing the blend of GPS height and heave so as to accurately present instantaneous height of transducer, is developed. The software structure design, key techniques and main function modules including quality control, time synchronization, attitude correction, as well as signal extraction and blend are depicted in detail. Moreover, the software is tested and applied in the actual experiments. The results show that the accuracy and performance of the software are high and can satisfy the actual application.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127433727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603968
K. Reichert, J. Dannenberg, Henk J. J. van den Boom
Nautical X-Band radars used for navigation can also be used to determine spectral and individual wave properties. The sea surface reflects the incident radar beams and wave fronts become visible as stripe like pattern of high back scatter on the radar screen. When connected to a conventional nautical X-Band radar, the Wave Monitoring System WaMoS II exploits this imaging of waves to detect full directional wave spectra and to derive statistical sea state parameters as well as surface currents. WaMoS II is continuously improved with new features being developed. In particular, the sea surface elevation maps derived by WaMoS II allow to investigate and describe the spatial and temporal development of 3D ocean surface waves. The European Joint Industry Project ‘On board Wave and Motion Estimator (OWME)’ used this measurement technique to provide the wave information that is required to predict periods of quiescent vessel motions. A task that offers valuable support for various offshore operations like e.g. the tensioning of a tanker or the landing of a helicopter. This contribution gives an overview of the overall OWME system design showing first validation results, focusing on the method to derive wave trains using the WaMoS II system.
{"title":"X-Band radar derived sea surface elevation maps as input to ship motion forecasting","authors":"K. Reichert, J. Dannenberg, Henk J. J. van den Boom","doi":"10.1109/OCEANSSYD.2010.5603968","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603968","url":null,"abstract":"Nautical X-Band radars used for navigation can also be used to determine spectral and individual wave properties. The sea surface reflects the incident radar beams and wave fronts become visible as stripe like pattern of high back scatter on the radar screen. When connected to a conventional nautical X-Band radar, the Wave Monitoring System WaMoS II exploits this imaging of waves to detect full directional wave spectra and to derive statistical sea state parameters as well as surface currents. WaMoS II is continuously improved with new features being developed. In particular, the sea surface elevation maps derived by WaMoS II allow to investigate and describe the spatial and temporal development of 3D ocean surface waves. The European Joint Industry Project ‘On board Wave and Motion Estimator (OWME)’ used this measurement technique to provide the wave information that is required to predict periods of quiescent vessel motions. A task that offers valuable support for various offshore operations like e.g. the tensioning of a tanker or the landing of a helicopter. This contribution gives an overview of the overall OWME system design showing first validation results, focusing on the method to derive wave trains using the WaMoS II system.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114479346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603803
S. Sagar, M. Wettle
Mapping the shallow water bathymetry of aquatic environments such as the Great Barrier Reef presents a number of challenges, due to both the large area which it occupies and the widely dispersed and variable shallow water reef areas which characterize it.
{"title":"Mapping the fine-scale shallow water bathymetry of the Great Barrier Reef using ALOS AVNIR-2 data","authors":"S. Sagar, M. Wettle","doi":"10.1109/OCEANSSYD.2010.5603803","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603803","url":null,"abstract":"Mapping the shallow water bathymetry of aquatic environments such as the Great Barrier Reef presents a number of challenges, due to both the large area which it occupies and the widely dispersed and variable shallow water reef areas which characterize it.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"143 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120981710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603871
T. Maki, A. Kume, T. Ura, T. Sakamaki, Hideyuki Suzuki
Although the vast amount of information collected by AUVs brings significant benefit to oceanographic research, it is necessary to develop methods to analyze the large volumes of data, in order to avoid accumulation of unused information. Automatic data processing and analysis are key technologies necessary to cope with this problem. We propose a robust, automated method for detection and volume determination of tubeworm colonies using visual and geometric features obtained during underwater robotic surveys, on the condition that the position of the sensors are provided. The tubeworm is a characteristic benthos of hydrothermal vent fields. The proposed method achieves robustness against sensor noise by using both geometric and visual features for identification. First, the tubeworm candidates are obtained as a three-dimensional region between the measured bathymetry of the region and an estimation of the seafloor topology without tubeworms. Next, the tubeworm candidates are verified through frequency analysis of corresponding images. The performance of this method was verified using a data set obtained by the AUV Tri-Dog 1 at Tagiri vent field, Kagoshima bay in Japan.
{"title":"Autonomous detection and volume determination of tubeworm colonies from underwater robotic surveys","authors":"T. Maki, A. Kume, T. Ura, T. Sakamaki, Hideyuki Suzuki","doi":"10.1109/OCEANSSYD.2010.5603871","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603871","url":null,"abstract":"Although the vast amount of information collected by AUVs brings significant benefit to oceanographic research, it is necessary to develop methods to analyze the large volumes of data, in order to avoid accumulation of unused information. Automatic data processing and analysis are key technologies necessary to cope with this problem. We propose a robust, automated method for detection and volume determination of tubeworm colonies using visual and geometric features obtained during underwater robotic surveys, on the condition that the position of the sensors are provided. The tubeworm is a characteristic benthos of hydrothermal vent fields. The proposed method achieves robustness against sensor noise by using both geometric and visual features for identification. First, the tubeworm candidates are obtained as a three-dimensional region between the measured bathymetry of the region and an estimation of the seafloor topology without tubeworms. Next, the tubeworm candidates are verified through frequency analysis of corresponding images. The performance of this method was verified using a data set obtained by the AUV Tri-Dog 1 at Tagiri vent field, Kagoshima bay in Japan.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"55 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125991732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603958
L. Freitag, K. Ball, P. Koski, Sandipa Singh, E. Gallimore
A prototype system for connecting remote instruments to a cabled observatory is described. The system consists of base-station modems and a data acquisition system attached to the MBARI MARS observatory in 900 m water off Monterey, California, plus remote modems used for link testing. The objective of the system is to provide a drop-in capability to connect sensors on the sea-floor or on sub-sea moorings to a cabled node that would otherwise require an ROV to make a hard-wired connection. While ROV installations of sensor-to-node cables are practical for many instruments, the acoustic connection is a way of lowering the barrier to general access of cabled nodes.
{"title":"Acoustic communications for deep-ocean observatories: Results of initial testing at the MBARI MARS node","authors":"L. Freitag, K. Ball, P. Koski, Sandipa Singh, E. Gallimore","doi":"10.1109/OCEANSSYD.2010.5603958","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603958","url":null,"abstract":"A prototype system for connecting remote instruments to a cabled observatory is described. The system consists of base-station modems and a data acquisition system attached to the MBARI MARS observatory in 900 m water off Monterey, California, plus remote modems used for link testing. The objective of the system is to provide a drop-in capability to connect sensors on the sea-floor or on sub-sea moorings to a cabled node that would otherwise require an ROV to make a hard-wired connection. While ROV installations of sensor-to-node cables are practical for many instruments, the acoustic connection is a way of lowering the barrier to general access of cabled nodes.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123010595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603858
L. Hamilton
Classification and exploration of large geodata sets consisting of tens to hundreds of thousands of single valued curves, e.g. oceanic wave spectra and grain size distributions, is often made through use of features or proxy parameters extracted from the curves. Feature extraction is typically enabled through curve fitting, and hence implicit or explicit application of a statistical model. Principal Components Analysis (PCA) is commonly applied to the proxies or to the curves as a dimensional reduction measure, and the first few principal components are used as the final classification features. Statistical clustering is then applied to the selected proxies or principal components to produce groups or classes which best describe the properties of the proxy data set, usually in a least squares sense. A far simpler and model free technique is to directly cluster the curves themselves. The curves are essentially treated as geometric entities, and calculation of features or proxies is unnecessary. The methodology for this concept is outlined, and is demonstrated for several geodata sets, ranging in size from a hundred objects to several tens of thousands, and for spatial scales of several tens of metres to the South Pacific ocean basin.
{"title":"Statistical clustering Of curves in the geosciences - the answer to everything?","authors":"L. Hamilton","doi":"10.1109/OCEANSSYD.2010.5603858","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603858","url":null,"abstract":"Classification and exploration of large geodata sets consisting of tens to hundreds of thousands of single valued curves, e.g. oceanic wave spectra and grain size distributions, is often made through use of features or proxy parameters extracted from the curves. Feature extraction is typically enabled through curve fitting, and hence implicit or explicit application of a statistical model. Principal Components Analysis (PCA) is commonly applied to the proxies or to the curves as a dimensional reduction measure, and the first few principal components are used as the final classification features. Statistical clustering is then applied to the selected proxies or principal components to produce groups or classes which best describe the properties of the proxy data set, usually in a least squares sense. A far simpler and model free technique is to directly cluster the curves themselves. The curves are essentially treated as geometric entities, and calculation of features or proxies is unnecessary. The methodology for this concept is outlined, and is demonstrated for several geodata sets, ranging in size from a hundred objects to several tens of thousands, and for spatial scales of several tens of metres to the South Pacific ocean basin.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126898723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603591
Cheng Fang, S. Anstee
This paper considers offline algorithms for pre-mission path planning to achieve coverage of the seabed of a complex but well-characterised planar area using an autonomous underwater vehicle fitted with side-looking sonar. The vehicle can swim over terrain at constant altitude, but must follow a path constructed from straight line segments. Imagery collected during turns is not used. This paper discusses the preparation of boundaries for the survey area, the introduction of buffer zones for safety of vehicle navigation, the decomposition of the surveyable area into subareas using an approximation to the generalised Voronoi diagram, calculation of paths within sub-areas that allow for incomplete sonar coverage, and connection of sub-area paths with transits to obtain a mission plan.
{"title":"Coverage path planning for harbour seabed surveys using an autonomous underwater vehicle","authors":"Cheng Fang, S. Anstee","doi":"10.1109/OCEANSSYD.2010.5603591","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603591","url":null,"abstract":"This paper considers offline algorithms for pre-mission path planning to achieve coverage of the seabed of a complex but well-characterised planar area using an autonomous underwater vehicle fitted with side-looking sonar. The vehicle can swim over terrain at constant altitude, but must follow a path constructed from straight line segments. Imagery collected during turns is not used. This paper discusses the preparation of boundaries for the survey area, the introduction of buffer zones for safety of vehicle navigation, the decomposition of the surveyable area into subareas using an approximation to the generalised Voronoi diagram, calculation of paths within sub-areas that allow for incomplete sonar coverage, and connection of sub-area paths with transits to obtain a mission plan.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127877502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603593
Ji-Hong Li, Byungho Yoon, Seung-Sub Oh, Jungsan Cho, Jong-Geol Kim, Munjik Lee, Jungwoo Lee
P-SURO is a prototype autonomous underwater vehicle (AUV), which is under development as a test-bed for developing underwater technologies such as underwater vision, underwater navigation, and guidance. This vehicle is a hovering type with four thrusters mounted to steer its 6DOF underwater motion, a color camera is mounted at the vehicle's nose for underwater vision, and an AHRS combined with one depth sensor and three range sonars construct an inertial navigation system. In this paper, we report the details of constructions of the vehicle system, and its three core modules - vision module, navigation module, and control module.
{"title":"Development of an intelligent autonomous underwater vehicle, P-SURO","authors":"Ji-Hong Li, Byungho Yoon, Seung-Sub Oh, Jungsan Cho, Jong-Geol Kim, Munjik Lee, Jungwoo Lee","doi":"10.1109/OCEANSSYD.2010.5603593","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603593","url":null,"abstract":"P-SURO is a prototype autonomous underwater vehicle (AUV), which is under development as a test-bed for developing underwater technologies such as underwater vision, underwater navigation, and guidance. This vehicle is a hovering type with four thrusters mounted to steer its 6DOF underwater motion, a color camera is mounted at the vehicle's nose for underwater vision, and an AHRS combined with one depth sensor and three range sonars construct an inertial navigation system. In this paper, we report the details of constructions of the vehicle system, and its three core modules - vision module, navigation module, and control module.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126523161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603620
T. Pfuetzenreuter, Helge Renkewitz
Today a large number of autonomous underwater vehicles (AUVs) are evaluated or operated all over the world. Most of them use their own control systems created by the vehicle's manufacturer or scientists of different research areas. The Fraunhofer Application Center System Technology currently owns three underwater vehicles (both AUVs and remotely operated vehicles, ROVs), a forth is under development. All these vehicles have their individual control systems that are very different with respect to changing / creating software modules, mission planning and evaluation. These differences are one reason to develop a new software framework for underwater vehicles called ConSys.
{"title":"ConSys - a new software framework for underwater vehicles","authors":"T. Pfuetzenreuter, Helge Renkewitz","doi":"10.1109/OCEANSSYD.2010.5603620","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603620","url":null,"abstract":"Today a large number of autonomous underwater vehicles (AUVs) are evaluated or operated all over the world. Most of them use their own control systems created by the vehicle's manufacturer or scientists of different research areas. The Fraunhofer Application Center System Technology currently owns three underwater vehicles (both AUVs and remotely operated vehicles, ROVs), a forth is under development. All these vehicles have their individual control systems that are very different with respect to changing / creating software modules, mission planning and evaluation. These differences are one reason to develop a new software framework for underwater vehicles called ConSys.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131502538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-24DOI: 10.1109/OCEANSSYD.2010.5603540
Shi-bo Fan, Zhengping Feng, L. Lian
An architecture for collision free formation control of multiple autonomous underwater vehicles is proposed in this paper. Based upon blackboard communication, the architecture includes communication, motion control and environment interacting modules. Orderly-Quaternion sets and control matrix are defined for the design of accurate formation geometry. Formation changing rules are proposed based on sensor information at first, and control matrix and artificial potential method are then utilized in formation reconfiguration. Finally the proposed approach is verified by a simulation of a swarm of 8 AUV's moving through a constrained environment.
{"title":"Collision free formation control for multiple autonomous underwater vehicles","authors":"Shi-bo Fan, Zhengping Feng, L. Lian","doi":"10.1109/OCEANSSYD.2010.5603540","DOIUrl":"https://doi.org/10.1109/OCEANSSYD.2010.5603540","url":null,"abstract":"An architecture for collision free formation control of multiple autonomous underwater vehicles is proposed in this paper. Based upon blackboard communication, the architecture includes communication, motion control and environment interacting modules. Orderly-Quaternion sets and control matrix are defined for the design of accurate formation geometry. Formation changing rules are proposed based on sensor information at first, and control matrix and artificial potential method are then utilized in formation reconfiguration. Finally the proposed approach is verified by a simulation of a swarm of 8 AUV's moving through a constrained environment.","PeriodicalId":129808,"journal":{"name":"OCEANS'10 IEEE SYDNEY","volume":"473 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133415098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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