The goal of this study was to determine the year round movement patterns of American horseshoe crabs, Limulus polyphemus, in the Great Bay Estuary, New Hampshire （USA） by using acoustic telemetry to track the moveme...The goal of this study was to determine the year round movement patterns of American horseshoe crabs, Limulus polyphemus, in the Great Bay Estuary, New Hampshire （USA） by using acoustic telemetry to track the movements of 37 adult Limulus, for periods ranging from 2 to 31 months. During the winter （December-March） horseshoe crabs moved very little. In the spring, when water temperatures exceeded II^C, horseshoe crabs moved at least 1 km further up into the estuary to shallower subtidal areas about a month prior to spawning. The mean distance traveled during spring migrations was 2.6 ＋ 0.5 （n=20） km up the estuary. Mating occurred in May and June and during these months animals spent most of their time in shallow subtidal areas adjacent to mating beaches. In the summer （July-Augnst）, animals moved 1.5 ± 0.5 （n=26） km down the estuary, towards the ocean, and ranged widely, using extensive portions of the estuary. In the fall （September-November） movement was more limited （0.5 ± 0.5 km; n = 24） while animals settled into wintering locations, where they remained until spring. The mean annual linear range for all animals was 4.5 ± 0.3 km （n =35） and the maximum distance traveled by an individual horseshoe crab within one year was 9.2 km. There was no evidence that any of the horseshoe crabs tracked during this study left the estuary展开更多
This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework i...This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow （underwater acoustic images） is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.展开更多
The United Nations(UN)’s call for a decade of“ecosystem restoration”was prompted by the need to address the extensive impact of anthropogenic activities on natural ecosystems.Marine ecosystem restoration is increas...The United Nations(UN)’s call for a decade of“ecosystem restoration”was prompted by the need to address the extensive impact of anthropogenic activities on natural ecosystems.Marine ecosystem restoration is increasingly necessary due to increasing habitat degredation in deep waters(>200 m depth).At these depths,which are far beyond those accessible by divers,only established and emerging robotic platforms such as remotely operated vehicles(ROVs),autonomous underwater vehicles(AUVs),landers,and crawlers can operate through manipulators and multiparametric sensor arrays(e.g.,optoacoustic imaging,omics,and environmental probes).The use of advanced technologies for deep-sea ecosystem restoration can provide:①high-resolution three-dimensional(3D)imaging and acoustic mapping of substrates and key taxa,②physical manipulation of substrates and key taxa,③real-time supervision of remote operations and long-term ecological monitoring,and④the potential to work autonomously.Here,we describe how robotic platforms with in situ manipulation capabilities and payloads of innovative sensors could autonomously conduct active restoration and monitoring across large spatial scales.We expect that these devices will be particularly useful in deep-sea habitats,such as①reef-building cold-water corals,②soft-bottom bamboo corals,and③soft-bottom fishery resources that have already been damaged by offshore industries(i.e.,fishing and oil/gas).展开更多
Sound source localization has numerous applications such as detection and localization of mechanical or structural failures in vehicles and buildings or bridges, security systems, collision avoidance, and robotic visi...Sound source localization has numerous applications such as detection and localization of mechanical or structural failures in vehicles and buildings or bridges, security systems, collision avoidance, and robotic vision. The paper presents the design of an anechoic chamber, sensor arrays and an analysis of how the data acquired from the sensors could be used for sound source localization and object detection. An anechoic chamber is designed to create a clean environment which isolates the experiment from external noises and reverberation echoes. An FPGA based data acquisition system is developed for a flexible acoustic sensor array platform. Using this sensor platform, we investigate direction of arrival estimation and source localization experiments with different geometries and with different numbers of sensors. We further present a discussion of parameters that influence the sensitivity and accuracy of the results of these experiments.展开更多
基金supported by National Science Foundation grants NSF lOB 0517229 and NSF IOS 0920342 to WHW Ⅲ and CCC
文摘The goal of this study was to determine the year round movement patterns of American horseshoe crabs, Limulus polyphemus, in the Great Bay Estuary, New Hampshire （USA） by using acoustic telemetry to track the movements of 37 adult Limulus, for periods ranging from 2 to 31 months. During the winter （December-March） horseshoe crabs moved very little. In the spring, when water temperatures exceeded II^C, horseshoe crabs moved at least 1 km further up into the estuary to shallower subtidal areas about a month prior to spawning. The mean distance traveled during spring migrations was 2.6 ＋ 0.5 （n=20） km up the estuary. Mating occurred in May and June and during these months animals spent most of their time in shallow subtidal areas adjacent to mating beaches. In the summer （July-Augnst）, animals moved 1.5 ± 0.5 （n=26） km down the estuary, towards the ocean, and ranged widely, using extensive portions of the estuary. In the fall （September-November） movement was more limited （0.5 ± 0.5 km; n = 24） while animals settled into wintering locations, where they remained until spring. The mean annual linear range for all animals was 4.5 ± 0.3 km （n =35） and the maximum distance traveled by an individual horseshoe crab within one year was 9.2 km. There was no evidence that any of the horseshoe crabs tracked during this study left the estuary
基金supported by the National Natural Science Foundation of China(Grant No.51009040)Heilongjiang Postdoctoral Fund(Grant No.LBH-Z11205)+1 种基金the National High Technology Research and Development Program of China(863 Program,Grant No.2011AA09A106)the China Postdoctoral Science Foundation(Grant No.2012M510928)
文摘This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow （underwater acoustic images） is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.
基金conceived within the preparation of the Project Restoration of Deep-sea habitats to Rebuild European Seas (REDRESS):HORIZON CL6-2023-BIODIV-Restoration of deepsea habitats carried out within the framework of the activities of the Spanish Government through the"Severo Ochoa Centre Excellence"granted to ICM-CSIC (CEX2019-000928-S)and the Research Unit Tecnoterra (ICM-CSIC/UPC)supported the work were those of the Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 of the Spanish government:BITER-LANDER (PID2020-114732RB-C32),BITER-ECO (PID2020-114732RB-C31),BITER-AUV (PID2020-114732RB-C33),PLOME (PLEC2021-007525/AEI/10.13039/501100011033)+3 种基金the conceptual development,falls within the framework of EU LIFE Project ECOREST (LIFE20 NAT/ES/001270)funded by a Juan de la Cierva Formación Post-doctoral Fellowship (FJC2021-047734-Ifinanced by Ministerio de Cuyltura e Innovación/Agencia Española de Investigación and European Union NextGeneration EU/PRTR funds)funded by the Spanish Government (Agencia Española de Investigación-AEI)through the‘Severo Ochoa Centre of Excellence’accreditation (CEX2019-000928-S).
文摘The United Nations(UN)’s call for a decade of“ecosystem restoration”was prompted by the need to address the extensive impact of anthropogenic activities on natural ecosystems.Marine ecosystem restoration is increasingly necessary due to increasing habitat degredation in deep waters(>200 m depth).At these depths,which are far beyond those accessible by divers,only established and emerging robotic platforms such as remotely operated vehicles(ROVs),autonomous underwater vehicles(AUVs),landers,and crawlers can operate through manipulators and multiparametric sensor arrays(e.g.,optoacoustic imaging,omics,and environmental probes).The use of advanced technologies for deep-sea ecosystem restoration can provide:①high-resolution three-dimensional(3D)imaging and acoustic mapping of substrates and key taxa,②physical manipulation of substrates and key taxa,③real-time supervision of remote operations and long-term ecological monitoring,and④the potential to work autonomously.Here,we describe how robotic platforms with in situ manipulation capabilities and payloads of innovative sensors could autonomously conduct active restoration and monitoring across large spatial scales.We expect that these devices will be particularly useful in deep-sea habitats,such as①reef-building cold-water corals,②soft-bottom bamboo corals,and③soft-bottom fishery resources that have already been damaged by offshore industries(i.e.,fishing and oil/gas).
文摘Sound source localization has numerous applications such as detection and localization of mechanical or structural failures in vehicles and buildings or bridges, security systems, collision avoidance, and robotic vision. The paper presents the design of an anechoic chamber, sensor arrays and an analysis of how the data acquired from the sensors could be used for sound source localization and object detection. An anechoic chamber is designed to create a clean environment which isolates the experiment from external noises and reverberation echoes. An FPGA based data acquisition system is developed for a flexible acoustic sensor array platform. Using this sensor platform, we investigate direction of arrival estimation and source localization experiments with different geometries and with different numbers of sensors. We further present a discussion of parameters that influence the sensitivity and accuracy of the results of these experiments.
