Journal articles: 'Autonomous surface vehicle (ASV)'

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Rathour, Swarn Singh, Naomi Kato, Naoto Tanabe, Hidetaka Senga, Yukino Hirai, Muneo Yoshie, and Toshinari Tanaka. "Spilled Oil Autonomous Tracking Using Autonomous Sea Surface Vehicle." Marine Technology Society Journal 49, no. 3 (May 1, 2015): 102–16. http://dx.doi.org/10.4031/mtsj.49.3.15.

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Abstract Over the past several decades, a concerted scientific effort has been made to estimate the drift and spread of spilled oil on the ocean surface. However, tracking spilled oil in open water remains challenging. This research focuses on the problem of autonomous oil spill tracking in oceanic marine environments. We describe a sensor-based guidance, navigation, and control system (GNCS) for oil spill tracking by an autonomous surface vehicle (ASV) in unsteady and uncertain environments. First, we describe the design and development of a yacht-shaped ASV that can track spilled oil on the sea surface using data supplied by onboard sensors to control rudder angle and sail area for navigation. Second, we evaluate the performance of a Ultraviolet/fluorometry-based optical sensor for use as an oil detection sensor. Third, we describe an autonomous ASV decision-making algorithm for target speed and direction based on a complete time history of the scanned area around the ASV by the oil detection sensor. Finally, we describe field experiments conducted at the Osaka University pond to validate the performance of the ASV with regard to autonomous oil spill tracking using GNCS based on onboard sensors data for tracking artificial oil targets. This technology has profound implications for oil spill disaster recovery operations.

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Herlambang, T., D. Rahmalia, A. Suryowinoto, F. Yudianto, F. A. Susanto, and M. Y. Anshori. "H-infinity for autonomous surface vehicle position estimation." Journal of Physics: Conference Series 2157, no. 1 (January 1, 2022): 012022. http://dx.doi.org/10.1088/1742-6596/2157/1/012022.

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Abstract Indonesia is a country with a very prominent marine charm, and it is the largest archipelago in the world, covering about 50% of the coral triangle area, providing marine tourist resorts. Therefore tourism development is quite promising. For that purpose, simple boats are of necessity for tourists to enjoy the beauty of such marine tourism. One solution to support such marine tourism sector is the availability of Autonomous Surface Vehicle (ASV). This vehicle will be the interest of this paper. This study used Touristant ASV with dimensions of 1.5 m in diameter, 4 meters in length and 1.3 meters in height. The purpose of this paper is to conduct a study with a focus on the estimation of ASV position with ASV motion influenced by wind speed and wave height by applying the H-infinity method. The position error generated from the simulation shows that the position error has an accuracy of about 96%.

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Ahmada, Alif Ihza, Wahyudi Wahyudi, and Eko Handoyo. "IMPLEMENTASI PENGENDALI PID UNTUK NAVIGASI AUTONOMOUS BERBASIS GLOBAL POSITIONING SYSTEM PADA PURWARUPA AUTONOMOUS SURFACE VEHICLE." Transient: Jurnal Ilmiah Teknik Elektro 9, no. 4 (November 17, 2020): 574–80. http://dx.doi.org/10.14710/transient.v9i4.574-580.

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Indonesia merupakan negara kepulauan yang meiliki wilayah peraian yang sangat luas, sehingga wilayah perairan yang harus dijaga juga sangat luas. Pada penelitian ini dirancang purwarupa sistem autonomous surface vehicle (ASV) yang kedepannya dapat digunakan untuk pengawasan wilayah perairan Indonesia. Perancangan sistem ASV meliputi perancangan perangkat keras yang digunakan dan perancangan pengendalian secara autonomous dengan pengendali Proporsional Integral Derifatif (PID) untuk mengendalikan motor servo. Perangkat keras yang digunakan untuk navigasi secara autonomous meliputi GPS receiver dan sensor magnetometer LIS3MDL. Sensor magnetometer digunakan sebagai umpan balik pengendali PID dan GPS receiver digunakan untuk mengetahui posisi dari ASV secara real time. Navigasi autonomous dilakukan dengan memberikan perintah berupa waypoint ke ASV. Pengendali PID akan membuat ASV mengikuti waypoint yang diberikan secara autonomous. Perancangan Pengendali PID dengan metode tuning trial and error didapatkan parameter Kp 1,5, Ki 0,3, dan Kd 0,2. Hasil pengujian PID yang dilakukan menunjukkan ASV dapat mencapai setpoint dalam waktu rata-rata selama 4,06 detik. Pengujian sistem kendali PID pada ASV dilakukan dengan beberapa bentuk lintasan, yaitu zigzag, bujur sangkar, dan sembarang. ASV dapat menyelesaikan misi pada setiap lintasan yang diberikan.

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Agustianto, Khafiddurrohman, and Dyah Ayu Dwijayanti. "Autonomous Surface Vehicle Controlling Menggunakan Kinect untuk Observasi Terumbu Karang." Jurnal Teknologi Informasi dan Terapan 6, no. 2 (December 24, 2019): 85–92. http://dx.doi.org/10.25047/jtit.v6i2.119.

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Autonomous Surface Vehicles (ASV) is a platform that is capable of recognizing oceanographic data that is moving on the surface of the sea. The ASV is commonly controlled using a remote RC, smartphones, joysticks, and keyboards. The development of control system innovations in the form of NUI, then ASV can be controlled using Kinect by someone without having to touch the remote. The study developed a marker-less ASV control using the Kinect skeleton feature to get the coordinate value to be the angle value of the right and left hand movement in the implemation as the value of the input fuzzy sugeno algorithm, which resulted in PWM speed output value. This marker-less development communicates wirelessly using the Xbee Pro S28 received by the Arduino Mega for communication and processing the running brushless motor and the ASV generates the movement according to the value received. Effect of light on Kinect in the efficient skeleton tracking process in the room maximum 53105 lux, and in the room maximum 201 lux. Object Spacing (Brainware) to read in the tracking process of the Kinect position of the efficient at a height of 120cm, and angle 00. Kinect communication distance with ASV reaches up to 10000cm. The success of a fuzzy calculation with the result of the movement of the ASV robot is 89.9%.

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Kitowski, Zygmunt. "System Architecture of Mission Planning and Autonomous Surface Vessel Control." Solid State Phenomena 210 (October 2013): 252–57. http://dx.doi.org/10.4028/www.scientific.net/ssp.210.252.

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The paper presents system architecture of mission planning and autonomous surface vehicle (ASV) "Edredon" control. The modular structure of the system makes possible realization of many tasks related to an ASV management. Due to appropriate configuration of its modules, it can perform such tasks as: mission planning on the command post, autonomous control of an ASV, as well as to serve as a training simulator for operators training and a simulator for ASVs control algorithms evaluation.

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Ibrahim, Ibrahim, Wahyudi Wahyudi, and Eko Handoyo. "PERANCANGAN TELECONTROLLING DAN TELEMETERING PADA GROUND CONTROL STATION UNTUK PURWARUPA AUTONOMOUS SURFACE VEHICLE." Transient: Jurnal Ilmiah Teknik Elektro 9, no. 4 (December 17, 2020): 581–88. http://dx.doi.org/10.14710/transient.v9i4.581-588.

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Ground Control Station (GCS) digunakan untuk mengendalikan dan memantau sebuah kendaraan tanpa awak secara nirkabel. GCS dirancang agar mampu memberikan informasi dan kendali yang cukup, sehingga misi yang diberikan kepada Autonomous Surface Vehicle (ASV) dapat terlaksana secara autonomous dengan intervensi telecontrolling yang minimal dari operator. Penelitian ini membahas mengenai perancangan GCS dalam mengoperasikan sebuah ASV. Microsoft Visual Studio Express 2012 digunakan dalam pengembangan perangkat lunak GCS. Modul telemetri radio 3DR 433Mhz digunakan sebagai media komunikasi antara GCS dan ASV. Berdasarkan pengujian, jarak optimal penggunaan modul radio 3DR 433Mhz untuk mengirim dan menerima data adalah 100 meter. Fitur telecontrolling pada GCS yang dirancang berupa parameter kecepatan, start/stop ASV, tuning PID, waypoint, dan failsafe. Fitur telemetering pada GCS yang dirancang berupa data latitude, longitude, heading, bearing, error hadap, jarak ASV ke waypoint selanjutnya, juga umpan balik PWM, state misi, nilai Kp, Ki, Kd, Sp, dan failsafe. Fitur lain pada GCS adalah menampilkan peta hybrid dan menyimpan data ASV dalam dokumen csv.

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Wang, Hongjian, Linlin Wang, and Lixin Pan. "Research on Roll Stabilizing Based on Energy Optimization for Autonomous Surface Vehicle." Journal of Applied Mathematics 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/347589.

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Considering the case of ASV (autonomous surface vehicle) navigating with low speed near water surface, a new method for design of roll motion controller is proposed in order to restrain wave disturbance effectively and improve roll stabilizing performance. Control system design is based on GPC (general predictive control) theory and working principle of zero-speed fin stabilizer. Coupling horizontal motion model of ASV is decoupled, and an equivalent transfer function of roll motion is obtained and transformed into a discrete difference equation through inverse Laplace transformation and Euler approximation. Finally, predictive model of GPC, namely, the difference equation of roll motion, is given. GPC algorithm of ASV roll motion is derived from performance index based on roll stabilizing performance and energy consumption used for driving fin stabilizer. In allusion to time-variant parameters in roll motion model, recursive least square method is adopted for parameter estimation. Simulation results of ASV roll motion control show better stabilizing performance and minimized energy consumption improved by self-adaptive GPC.

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Nurhadi, Hendro, Erna Apriliani, Teguh Herlambang, and Dieky Adzkiya. "Sliding mode control design for autonomous surface vehicle motion under the influence of environmental factor." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 5 (October 1, 2020): 4789. http://dx.doi.org/10.11591/ijece.v10i5.pp4789-4797.

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Autonomous Surface Vehicle (ASV) is a vehicle that is operated in the water surface without any person in the vehicle. Since there is no person in the ASV, a motion controller is essentially needed. The control system is used to make sure that the water vehicle is moving at the desired speed. In this paper, we use a Touristant ASV with the following specifications: the length is 4 meters, the diameter is 1.625 meters, and the height is 1.027 meters. The main contribution of this paper is applying the Sliding Mode Control system to the Touristant ASV model under the influence of environmental factors. The environmental factors considered in this work are wind speed and wave height. The Touristant ASV model is nonlinear and uses three degree of freedom (DOF), namely surge, sway and yaw. The simulation results show that the performance of the closed-loop system by using the SMC method depends on the environmental factors. If environmental factors are higher, then the resulting error is also higher. The average error difference between those resulted from the simulation without environmental factors and those with the influence of environmental factors is 0.05% for surge, sway and yaw motions.

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Kitowski, Zygmunt. "Mission Planning Training Simulator of Autonomous Surface Vehicle (ASV)." Applied Mechanics and Materials 817 (January 2016): 168–76. http://dx.doi.org/10.4028/www.scientific.net/amm.817.168.

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The paper presents the architecture of the mission planning training simulator of the autonomous surface vehicle (ASV) "Edredon". The structure of the simulator is based on a mission planning site, designed by the Polish-Japanese School of Computing, located in the USV command post. Its software allows not only for planning the ASV’s route but also for implementing the training process of an operator preparing the route.

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Lee, Dongwoo, and Joohyun Woo. "Reactive Collision Avoidance of an Unmanned Surface Vehicle through Gaussian Mixture Model-Based Online Mapping." Journal of Marine Science and Engineering 10, no. 4 (March 27, 2022): 472. http://dx.doi.org/10.3390/jmse10040472.

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With active research being conducted on maritime autonomous surface ships, it is becoming increasingly necessary to ensure the safety of unmanned surface vehicles (USVs). In this context, a key task is to correct their paths to avoid obstacles. This paper proposes a reactive collision avoidance algorithm to ensure the safety of USVs against obstacles. A global map is represented using a Gaussian mixture model, formulated using the expectation–maximization algorithm. Motion primitives are used to predict collision events and modify the USV’s trajectory. In addition, a controller for the target vessel is designed. Mapping is performed to demonstrate that the USV can implement the necessary avoidance maneuvers to prevent collisions with obstacles. The proposed method is validated by conducting collision avoidance simulations and autonomous navigation field tests with a small-scale autonomous surface vehicle (ASV) platform. Results indicate that the ASV can successfully avoid obstacles while following its trajectory.

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D’Angelo, Vincenzo, Paolo Folino, Marco Lupia, Gianfranco Gagliardi, Gianni Cario, Francesco Cicchello Gaccio, and Alessandro Casavola. "A ROS-Based GNC Architecture for Autonomous Surface Vehicle Based on a New Multimission Management Paradigm." Drones 6, no. 12 (November 27, 2022): 382. http://dx.doi.org/10.3390/drones6120382.

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This paper presents the design and implementation of BAICal (Intelligent Autonomous Buoy by the University of Calabria), an autonomous surface vehicle (ASV) developed at the Autonomous Systems Lab (LASA) of the Department of Computer Science, Modeling, Electronics, and Systems Engineering (DIMES), University of Calabria. The basic project was born as a research program in marine robotics with multiple applications, either in the sea or in lake/river environments, for data monitoring, search and rescue operations and diver support tasks. Mechanical and hardware designs are discussed by considering a three-degree-of-freedom (3DoF) dynamical model of the vehicle. An extension to the typical guidance, navigation, and control (GNC) software architecture is presented. The software design and the implementation of a manager module (M-GNC architecture) that allows the vehicle to autonomously coordinate missions are described. Indeed, autonomous guidance and movement are only one of several more complex tasks that mobile robots have to perform in a real scenario and that allow a long-term life cycle. Module-based software architecture is developed by using the Robot Operating System (ROS) framework that is suitable for different kinds of autonomous vehicles, such as aerial, ground, surface or underwater drones.

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Dong, N., N. H. Nam, K. M. Tuan, and N. V. Hien. "A Novel Approach to Model and Implement Planar Trajectory-Tracking Controllers for AUVs/ASVs." Advanced Materials Research 1016 (August 2014): 686–93. http://dx.doi.org/10.4028/www.scientific.net/amr.1016.686.

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Following the Model-Driven Architecture (MDA) approach, we have modeled and implemented a planar trajectory planning and tracking controller designed for Autonomous Underwater Vehicles or Autonomous Surface Vessels (AUVs/ASVs). Our approach covers steps such as the requirement, analysis, design and implementation to model and realize a controller for most standard AUV/ASV platforms. It also allows the designed elements to be customizable and re-usable in the development of new applications of AUV/ASV controllers. The paper describes step-by-step the development lifecycle of planar trajectory-tracking controller for AUVs/ASVs. Based on this approach, a horizontal trajectory-tracking controller of a miniature autonomous submerged vehicle is completely developed and successfully taken on trial trip.

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Stateczny, Andrzej, Witold Kazimierski, Daria Gronska-Sledz, and Weronika Motyl. "The Empirical Application of Automotive 3D Radar Sensor for Target Detection for an Autonomous Surface Vehicle’s Navigation." Remote Sensing 11, no. 10 (May 14, 2019): 1156. http://dx.doi.org/10.3390/rs11101156.

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Avoiding collisions with other objects is one of the most basic safety tasks undertaken in the operation of floating vehicles. Addressing this challenge is essential, especially during unmanned vehicle navigation processes in autonomous missions. This paper provides an empirical analysis of the surface target detection possibilities in a water environment, which can be used for the future development of tracking and anti-collision systems for autonomous surface vehicles (ASV). The research focuses on identifying the detection ranges and the field of view for various surface targets. Typical objects that could be met in the water environment were analyzed, including a boat and floating objects. This study describes the challenges of implementing automotive radar sensors for anti-collision tasks in a water environment from the perspective of target detection with the application for small ASV performing tasks on the lake.

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Groves, Keir, Andrew West, Konrad Gornicki, Simon Watson, Joaquin Carrasco, and Barry Lennox. "MallARD: An Autonomous Aquatic Surface Vehicle for Inspection and Monitoring of Wet Nuclear Storage Facilities." Robotics 8, no. 2 (June 18, 2019): 47. http://dx.doi.org/10.3390/robotics8020047.

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Inspection and monitoring of wet nuclear storage facilities such as spent fuel pools or wet silos is performed for a variety of reasons, including nuclear security and characterisation of storage facilities prior to decommissioning. Until now such tasks have been performed by personnel or, if the risk to health is too high, avoided. Tasks are often repetitive, time-consuming and potentially dangerous, making them suited to being performed by an autonomous robot. Previous autonomous surface vehicles (ASVs) have been designed for operation in natural outdoor environments and lack the localisation and tracking accuracy necessary for operation in a wet nuclear storage facility. In this paper the environmental and operational conditions are analysed, applicable localisation technologies selected and a unique aquatic autonomous surface vehicle (ASV) is designed and constructed. The ASV developed is holonomic, uses a LiDAR for localisation and features a robust trajectory tracking controller. In a series of experiments the mean error between the present ASV’s planned path and the actual path is approximately 1 cm, which is two orders of magnitude lower than previous ASVs. As well as lab testing, the ASV has been used in two deployments, one of which was in an active spent fuel pool.

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Martorell-Torres, Antoni, Eric Guerrero-Font, José Guerrero-Sastre, and Gabriel Oliver-Codina. "Xiroi II, an Evolved ASV Platform for Marine Multirobot Operations." Sensors 23, no. 1 (December 22, 2022): 109. http://dx.doi.org/10.3390/s23010109.

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In this paper, we present the design, development and a practical use of an Autonomous Surface Vehicle (ASV) as a modular and flexible platform for a large variety of marine tasks including the coordination strategies with other marine robots. This work tackles the integration of an open-source Robot-Operating-System (ROS)-based control architecture that provides the ASV with a wide variety of navigation behaviors. These new ASV capabilities can be used to acquire useful data from the environment to survey, map, and characterize marine habitats. In addition, the ASV is used as a radio frequency relay point between an Autonomous Underwater Vehicle (AUV) and the ground station as well as to enhance the Acoustic Communication Link (ACL) with the AUV. In order to improve the quality of the ACL, a new Marine Multirobot System (MMRS) coordination strategy has been developed that aims to keep both vehicles close to each other. The entire system has been successfully designed, implemented, and tested in real marine environment robotic tasks. The experimental tests show satisfactory results both in ROS-based navigation architecture and the MMRS coordination strategy resulting in a significant improvement of the quality of the ACL.

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Tall, M. H., P. F. Rynne, J. M. Lorio, and K. D. von Ellenrieder. "Visual-Based Navigation of an Autonomous Surface Vehicle." Marine Technology Society Journal 44, no. 2 (March 1, 2010): 37–45. http://dx.doi.org/10.4031/mtsj.44.2.6.

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AbstractThis paper presents the work of a team of undergraduate and graduate students at Florida Atlantic University (FAU) who compete in the annual Autonomous Surface Vehicle (ASV) competition held jointly by the Association for Unmanned Vehicle Systems International (AUVSI) and the U.S. Office of Naval Research (ONR). The conceptual design of the vehicle, its physical realization, and the results of both preliminary testing and the final competition are presented. The initial configuration of a stereoscopic vision system and navigation algorithm is explored through testing in a controlled environment. With this approach, the vehicle is shown to be capable of navigating through various courses of colored buoys; approximately 25% of the attempts result in successful navigation of all buoy pairs while 75% of the attempts result in successful navigation of half the buoy pairs or more.

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Nugroho, C. A., A. Vidura, M. R. Rahman, M. Iqbal, M. G. A. Satria, and I. Jaya. "Implementation of swarm intelligence algorithm on Autonomous Surface Vehicle (ASV)." IOP Conference Series: Earth and Environmental Science 429 (January 28, 2020): 012045. http://dx.doi.org/10.1088/1755-1315/429/1/012045.

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Martorell-Torres, Antoni, Miquel Massot-Campos, Eric Guerrero-Font, and Gabriel Oliver-Codina. "Xiroi ASV: a Modular Autonomous Surface Vehicle to Link Communications." IFAC-PapersOnLine 51, no. 29 (2018): 147–52. http://dx.doi.org/10.1016/j.ifacol.2018.09.484.

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Cuppens, A., G. Menesse, E. Caligaris, O. Marecos, and G. Wyseure. "A low-cost, open-source autonomous surface vehicle as a multipurpose waste stabilization pond monitoring platform." Journal of Water, Sanitation and Hygiene for Development 9, no. 1 (November 7, 2018): 172–80. http://dx.doi.org/10.2166/washdev.2018.110.

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Abstract Although waste stabilization ponds (WSPs) are widely used in developing countries, monitoring data on their operational performance are scarce. Traditional methods for monitoring in-pond conditions, i.e. conducting hand held measurements from a small boat or installing fixed sensor networks, are not straightforward to realize and create an unhealthy working environment for field workers. A promising technology for the safe and efficient collection of monitoring data is a compact autonomous surface vehicle (ASV), capable of autonomous navigation along a predefined trajectory based on geographic coordinates and measurements in different places and depths. In this practical paper, the development process, technical details and functional testing results of a low-cost ASV for WSP monitoring are presented. Commonly available construction materials and electronic components were used to ensure affordability and reparability. The access to online tutorials and peer-support was crucial for assembling the open-source autopilot and data logger. The ASV demonstrated satisfactory performance for both the autonomous navigation as well as the georeferenced data logging of measurements at a real-scale WSP in Paraguay. This study demonstrates how the adoption of open-source hardware and software offers the flexibility for the wastewater professionals to develop customized DIY solutions for specific monitoring applications and working environments.

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Brown, Hunter C., Liza K. Jenkins, Guy A. Meadows, and Robert A. Shuchman. "BathyBoat: An Autonomous Surface Vessel for Stand-alone Survey and Underwater Vehicle Network Supervision." Marine Technology Society Journal 44, no. 4 (July 1, 2010): 20–29. http://dx.doi.org/10.4031/mtsj.44.4.5.

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AbstractExploration of remote environments, once the domain of intrepid adventurers, can now be conducted in relative safety using unmanned vehicles. This article describes the joint University of Michigan (UMich) and Michigan Tech Research Institute’s project to design and to build a new autonomous surface vessel (ASV) for use in research, education, and resource management as well as in the commercial sector.Originally designed to assist with bathymetric surveys in the wilderness of northern Alaska, the BathyBoat has become a test-bed platform for new research in collaborative heterogeneous underwater robotic search and survey missions in ports, harbors, lakes, and rivers. The UMich Marine Hydrodynamics Laboratories are actively researching autonomous technologies such as cooperative navigation, surface vessel control, and multivehicle search and survey using the BathyBoat and the UMich Perceptual Robotics Laboratory’s Iver2 autonomous underwater vehicles.This article presents an overview of these research topics and highlights relevant real-world testing and recent missions involving the BathyBoat ASV on Alaska’s North Slope, the harbors of Illinois, and various riverine environments in Michigan.

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Zube, Angelika, Dominik Kleiser, Alexander Albrecht, Philipp Woock, Thomas Emter, Boitumelo Ruf, Igor Tchouchenkov, et al. "Autonomously mapping shallow water environments under and above the water surface." at - Automatisierungstechnik 70, no. 5 (May 1, 2022): 482–95. http://dx.doi.org/10.1515/auto-2021-0145.

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Abstract The paper describes an autonomous water vehicle (ASV) capable of autonomously mapping shallow water environments above and below the water surface. Over the past two years, Fraunhofer IOSB has developed a system that is fully electrified and equipped with extensive sensor technology (multibeam sonar, lidar, cameras, IMU, GNSS). For autonomous navigation, the complete processing pipeline was implemented, from obstacle detection and avoidance to trajectory planning and control to multi-sensor localization and mapping. Above water, both lidar-based mapping and photogrammetric methods are used; underwater, bathymetry data is obtained using sonar. The interface to the operator is realized by an interactive digital map table, which allows intuitive mission specification and evaluation.

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Passarella, R., A. Zarkasi, H. Maghfur, Sutarno, K. Exsaudi, APP Prasetyo, and H. Veny. "Autonomous Surface Vehicle (ASV) Obstacle Avoidance Using Fuzzy Kohonen Network (FKN)." IOP Conference Series: Materials Science and Engineering 648 (October 18, 2019): 012023. http://dx.doi.org/10.1088/1757-899x/648/1/012023.

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Jung, Jongdae, Yeongjun Lee, Jeonghong Park, and Tae-Kyeong Yeu. "Multi-Modal Sonar Mapping of Offshore Cable Lines with an Autonomous Surface Vehicle." Journal of Marine Science and Engineering 10, no. 3 (March 3, 2022): 361. http://dx.doi.org/10.3390/jmse10030361.

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Monitoring offshore infrastructure is a challenging task owing to the harsh ocean environment. To reduce human involvement in this task, this study proposes an autonomous surface vehicle (ASV)-based structural monitoring system for inspecting power cable lines under the ocean surface. The proposed ASV was equipped with multimodal sonar sensors, including a multibeam echosounder (MBES) and side-scan sonar (SSS) for mapping the seafloor, combined with a precisely estimated vehicle pose from navigation sensors. In particular, a globally consistent map was developed using the orthometric height as a vertical datum estimated based on the geoid height received from the GPS. Accordingly, the MBES and SSS generate a map of the target objects in the form of point clouds and sonar images, respectively. Dedicated outlier removal methods for MBES sensing were proposed to preserve the sparse inlier point cloud, and we applied the projection of the SSS image pixels to reflect the geometry of the seafloor. A field test was conducted in an ocean environment using real offshore cable lines to verify the efficiency of the proposed monitoring system.

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Ohki, Takeshi, Hitoshi Kakami, Yuya Nishida, Takeshi Nakatani, and Blair Thornton. "Development and Testing of an Unmanned Surface Towing System for Autonomous Transport of Multiple Heterogeneous Underwater Vehicles for Seafloor Survey." Marine Technology Society Journal 54, no. 5 (September 1, 2020): 61–71. http://dx.doi.org/10.4031/mtsj.54.5.10.

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AbstractSimultaneous operation of multiple autonomous underwater vehicles (AUVs) can increase seafloor mapping efficiency. However, AUVs typically rely on support vessels with an operations crew for transport to sites of interest and supervision during their dives. This is costly and limits the scalability of AUV-based seafloor mapping. This paper describes a robotic system that can transport AUVs from shore and deploy them in a survey area located offshore, without the need for a crewed support vessel. We clarify the functional requirements for ship-free AUV operations and propose a concept that allows a single autonomous surface vehicle (ASV) to transport, release, and monitor multiple large and heterogeneous AUVs. The proposed system uses towing modules that can be connected in parallel and can accommodate a variety of pre-existing ASVs and AUVs. A full-scale system was developed and tested during sea trials in the Mediterranean Sea off Greece, to verify basic functionality and gather data on the impact of towing multiple AUVs on ASV endurance and range. Results of these trials and lessons learned are discussed.

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Herlambang, Teguh, Diecky Adzkiya, and Hendro Nurhadi. "OPTIMIZATION OF TOURISTANT ASV WITH JACOBIAN APPROACH." JOURNAL ASRO 10, no. 2 (July 24, 2019): 100. http://dx.doi.org/10.37875/asro.v10i2.133.

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An Autonomous Surface Vehicle (ASV) is an unmanned ship that can automatically navigate itself in watery area. ASV can be utilized as tourism modes, transportation modes, Indonesian military (TNI) fleets or warships. In this paper, the study used a Touristant ASV prototype with a length of 3 meters, a diameter of 1.5 meters, and a height of 1.3 meters. The ASV motion system is a linear model with 3-DOF (surge, sway and yaw), resulted from the linearization of the ASV nonlinear model into a linear model which, then, was optimized as the basis of the navigation and guidance control system. The objective of this paper is to check the controllability and observability of the ASV Touristant linear model. The contribution of this paper is to provide numeric study on the controllability and observability of the model. Keyword: ASV, 3-DOF, linear model, Optimization, Controlable, Observable

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Riahifard, Hosseini Rostami, Wang, and Kim. "Adaptive Leader-Follower Formation Control of Under-actuated Surface Vessels with Model Uncertainties and Input Constraints." Applied Sciences 9, no. 18 (September 17, 2019): 3901. http://dx.doi.org/10.3390/app9183901.

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This paper deals with the leader-follower formation control of underactuated autonomous surface vehicles in the presence of model uncertainties and input constraints. In a leader-follower formation, an autonomous surface vehicle (ASV) called leader tracks a pre-described trajectory and other ASVs called followers that are controlled to follow the leader with a desired distance and desired relative bearing. To this end, some adaptive robust techniques are adopted to guarantee the robustness of the closed-loop system against model uncertainties, external disturbances, and input saturation constraints. Based on the Lyapunov synthesis, it is proven that with the developed formation controllers, the closed-loop system is stable and all the formation errors converge to a small neighborhood of zero. Simulation results demonstrate the effectiveness of the proposed method.

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Esfahani, Hossein Nejatbakhsh, and Rafal Szlapczynski. "Model Predictive Super-Twisting Sliding Mode Control for an Autonomous Surface Vehicle." Polish Maritime Research 26, no. 3 (September 1, 2019): 163–71. http://dx.doi.org/10.2478/pomr-2019-0057.

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Abstract This paper presents a new robust Model Predictive Control (MPC) algorithm for trajectory tracking of an Autonomous Surface Vehicle (ASV) in presence of the time-varying external disturbances including winds, waves and ocean currents as well as dynamical uncertainties. For fulfilling the robustness property, a sliding mode control-based procedure for designing of MPC and a super-twisting term are adopted. The MPC algorithm has been known as an effective approach for the implementation simplicity and its fast dynamic response. The proposed hybrid controller has been implemented in MATLAB / Simulink environment. The results for the combined Model Predictive Super-Twisting Sliding Mode Control (MP-STSMC) algorithm have shown that it significantly outperforms conventional MPC algorithm in terms of the transient response, robustness and steady state response and presents an effective chattering attenuation in comparison with the Super-Twisting Sliding Mode Control (STSMC) algorithm.

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Wu, Gongxing, Yuchao Li, Chunmeng Jiang, Chao Wang, Jiamin Guo, and Rui Cheng. "MULTI-VESSELS COLLISION AVOIDANCE STRATEGY FOR AUTONOMOUS SURFACE VEHICLES BASED ON GENETIC ALGORITHM IN CONGESTED PORT ENVIRONMENT." Brodogradnja 73, no. 3 (July 1, 2022): 69–91. http://dx.doi.org/10.21278/brod73305.

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An improved genetic collision avoidance algorithm is proposed in this study to address the problem that Autonomous Surface Vehicles (ASV) need to comply with the collision avoidance rules at sea in congested sea areas. Firstly, a collision risk index model for ASV safe encounters is established taking into account the international rules for collision avoidance. The ASV collision risk index and the distance of safe encounters are taken as boundary values of the correlation membership function of the collision risk index model to calculate the optimal heading of ASV in real-time. Secondly, the genetic coding, fitness function, and basic parameters of the genetic algorithm are designed to construct the collision avoidance decision system. Finally, the simulation of collision avoidance between ASV and several obstacle vessels is performed, including the simulation of three collision avoidance states head-on situation, crossing situation, and overtaking situation. The results show that the proposed intelligent genetic algorithm considering the rules of collision avoidance at sea can effectively avoid multiple other vessels in different situations.

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Stateczny, Andrzej, Witold Kazimierski, Paweł Burdziakowski, Weronika Motyl, and Marta Wisniewska. "Shore Construction Detection by Automotive Radar for the Needs of Autonomous Surface Vehicle Navigation." ISPRS International Journal of Geo-Information 8, no. 2 (February 13, 2019): 80. http://dx.doi.org/10.3390/ijgi8020080.

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Autonomous surface vehicles (ASVs) are becoming more and more popular for performing hydrographic and navigational tasks. One of the key aspects of autonomous navigation is the need to avoid collisions with other objects, including shore structures. During a mission, an ASV should be able to automatically detect obstacles and perform suitable maneuvers. This situation also arises in near-coastal areas, where shore structures like berths or moored vessels can be encountered. On the other hand, detection of coastal structures may also be helpful for berthing operations. An ASV can be launched and moored automatically only if it can detect obstacles in its vicinity. One commonly used method for target detection by ASVs involves the use of laser rangefinders. The main disadvantage of this approach is that such systems perform poorly in conditions with bad visibility, such as in fog or heavy rain. Therefore, alternative methods need to be sought. An innovative approach to this task is presented in this paper, which describes the use of automotive three-dimensional radar on a floating platform. The goal of the study was to assess target detection possibilities based on a comparison with photogrammetric images obtained by an unmanned aerial vehicle (UAV). The scenarios considered focused on analyzing the possibility of detecting shore structures like berths, wooden jetties, and small houses, as well as natural objects like trees or other kinds of vegetation. The recording from the radar was integrated into a single complex radar image of shore targets. It was then compared with an orthophotomap prepared from AUV camera pictures, as well as with a map based on traditional land surveys. The possibility and accuracy of detection for various types of shore structure were statistically assessed. The results show good potential for the proposed approach—in general, objects can be detected using the radar—although there is a need for development of further signal processing algorithms.

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Shamsuddin, Putri Nur Farhanah Mohd, Roshahliza M. Ramli, and Muhamad Arifpin Mansor. "Navigation and motion control techniques for surface unmanned vehicle and autonomous ground vehicle: a review." Bulletin of Electrical Engineering and Informatics 10, no. 4 (August 1, 2021): 1893–904. http://dx.doi.org/10.11591/eei.v10i4.3086.

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An excellent navigation, guidance, and control (NGC) system had a high impact on trajectory tracking and the following scenarios. Both scenarios will include the heading, tangent, and velocity parameters in the computation. However, the control system design problem is not a new issue in the unmanned surface vehicle (USV) and autonomous ground vehivle (AGV) due to this constraint faced by many researchers since early these autonomy developments. Hence, this paper listed and emphasizing the techniques, including techniques implementation, strength, and the algorithm's constraints, a fusion of several techniques implemented for vehicle's stability, a turning ahead, and heading estimation. This paper concerns the similar algorithm used in the USV and AGV. Most of the selected techniques are basic algorithms and have been frequently implemented to control both vehicles' systems. Previous research shows pure pursuit guidance is the most popular technique in AGV to control the degree-of-freedom (DOF) velocity and the dynamic rate (sway, surge, and yaw). Simultaneously, the line of sight (LOS) controller is very compatible with controlling the movement of the USV. In conclusion, the technique's simulation test needs further research that will expose in the actual situation.

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Thomson, Jim, James B. Girton, Rajesh Jha, and Andrew Trapani. "Measurements of Directional Wave Spectra and Wind Stress from a Wave Glider Autonomous Surface Vehicle." Journal of Atmospheric and Oceanic Technology 35, no. 2 (February 2018): 347–63. http://dx.doi.org/10.1175/jtech-d-17-0091.1.

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AbstractMethods for measuring waves and winds from a Wave Glider autonomous surface vehicle (ASV) are described and evaluated. The wave method utilizes the frequency spectra of orbital velocities measured by GPS, and the wind stress method utilizes the frequency spectra of turbulent wind fluctuations measured by an ultrasonic anemometer. Both methods evaluate contaminations from vehicle motion. The methods were evaluated with 68 days of data over a full range of open ocean conditions, in which wave heights varied from 1 to 8 m and wind speeds varied from 1 to 17 m s−1. Reference data were collected using additional sensors on board the vehicle. For the waves method, several additional datasets are included that use independently moored Datawell Waverider buoys as reference data. Bulk wave parameters are determined within 5% error with biases of less than 5%. Wind stress is determined within 4% error with 1% bias. Wave directional spectra also compare well, although the Wave Glider results have more spread at low frequencies.

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Odetti, Angelo, Marco Altosole, Gabriele Bruzzone, Massimo Caccia, and Michele Viviani. "Design and Construction of a Modular Pump-Jet Thruster for Autonomous Surface Vehicle Operations in Extremely Shallow Water." Journal of Marine Science and Engineering 7, no. 7 (July 15, 2019): 222. http://dx.doi.org/10.3390/jmse7070222.

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This paper describes a customized thruster for Autonomous Surface Vehicles (ASV). The thruster is a Pump-Jet Module (PJM), which has been expressly designed, modeled, constructed, and tested for small-/medium-sized ASVs that perform environmental monitoring in extremely shallow waters such as wetlands (rivers, lakes, swamps, marshes), where water depth is only a few centimeters. The PJM is a fully-electric propulsion unit with a 360-degree continuous steering capability. Its main advantage is that the unit is flush with the flat bottom of the vehicle. This makes the PJM suitable for operation in extremely shallow waters because the risk of damaging the thrusting unit in case of grounding is very limited. The PJM was produced using innovative materials, and the hydraulic components were all constructed using a 3D printer.

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Veitch, Erik, and Ole Andreas Alsos. "Human-Centered Explainable Artificial Intelligence for Marine Autonomous Surface Vehicles." Journal of Marine Science and Engineering 9, no. 11 (November 6, 2021): 1227. http://dx.doi.org/10.3390/jmse9111227.

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Explainable Artificial Intelligence (XAI) for Autonomous Surface Vehicles (ASVs) addresses developers’ needs for model interpretation, understandability, and trust. As ASVs approach wide-scale deployment, these needs are expanded to include end user interactions in real-world contexts. Despite recent successes of technology-centered XAI for enhancing the explainability of AI techniques to expert users, these approaches do not necessarily carry over to non-expert end users. Passengers, other vessels, and remote operators will have XAI needs distinct from those of expert users targeted in a traditional technology-centered approach. We formulate a concept called ‘human-centered XAI’ to address emerging end user interaction needs for ASVs. To structure the concept, we adopt a model-based reasoning method for concept formation consisting of three processes: analogy, visualization, and mental simulation, drawing from examples of recent ASV research at the Norwegian University of Science and Technology (NTNU). The examples show how current research activities point to novel ways of addressing XAI needs for distinct end user interactions and underpin the human-centered XAI approach. Findings show how representations of (1) usability, (2) trust, and (3) safety make up the main processes in human-centered XAI. The contribution is the formation of human-centered XAI to help advance the research community’s efforts to expand the agenda of interpretability, understandability, and trust to include end user ASV interactions.

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Lenain, Luc, and W. Kendall Melville. "Autonomous Surface Vehicle Measurements of the Ocean’s Response to Tropical Cyclone Freda." Journal of Atmospheric and Oceanic Technology 31, no. 10 (October 1, 2014): 2169–90. http://dx.doi.org/10.1175/jtech-d-14-00012.1.

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Abstract On 31 December 2012, an instrumented autonomous surface vehicle (ASV; Wave Glider) transiting across the Pacific from Hawaii to Australia as part of the Pacific Crossing (PacX) project came very close (46 km) to the center of a category 3 Tropical Cyclone (TC), Freda, experiencing winds of up to 37 and significant wave heights close to 10 m. The Wave Glider was instrumented for surface ocean–lower atmosphere (SOLA) measurements, including atmospheric pressure, surface winds and temperature, sea surface temperature, salinity, dissolved oxygen, fluorescence (chlorophyll-a and turbidity), and surface-wave directional spectra. Such measurements in close proximity to a tropical cyclone are rare. This study presents novel observations of the ocean’s response in three quadrants of TC Freda, collected from the instrumented glider. Evolution of the wind, the directional wave field, the sea surface temperature, and the Stokes drift profile (calculated from the wave directional spectrum) as Freda passed near the vehicle are examined. Results are discussed in the context of the recent coupled wind-wave modeling and large eddy simulation (LES) modeling of the marine boundary layer in Hurricane Frances (Sullivan et al. 2012). Processes by which cold nutrient-rich waters are entrained and mixed from below into the mixed layer as the TC passes near the Wave Glider are presented and discussed. The results of this encounter of an autonomous surface vehicle with TC Freda supports the use of ASVs for regular TC (hurricane) monitoring to complement remote sensing and “hurricane hunter” aircraft missions.

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Saputra, Noverdo, Muhammad Arifudin Lukmana, and Purwo Joko Suranto. "Development of an Automatic Anti Pitching System (APS) Autonomous Surface Vehicle (ASV) for Fish Mapping." Journal of Physics: Conference Series 1569 (July 2020): 032033. http://dx.doi.org/10.1088/1742-6596/1569/3/032033.

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Ahmad Fauzan, Zakki, Aris Triwiyatno, Bandi Sasmito, and Muhammad H. Nubly. "Intact stability and seakeeping characteristics of autonomous surface vehicle (asv) using swath hullform to support bathymetry survey activities on the coastal area." MATEC Web of Conferences 177 (2018): 01001. http://dx.doi.org/10.1051/matecconf/201817701001.

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The information is an important thing to search a new resource. In this decade, with leading-edge technology is easier to find any information about our earth. Thus, that is must be explored by the ships. The exploration works usually take a long time, and for convenience, the unmanned technology is much promised. In this research, we focused on the autonomous surface vehicle for bathymetry survey. To design the ASV, we must consider the reliability, efficiency, and safety. To reach those three components, the analysis of resistance, stability and wave response are necessary. Therefore, the hull form design is focused on Small Waterplane Area Twin Hull (SWATH) hull form. According to the numerical analysis, the proposed SWATH hull form of ASV is suitable for bathymetry activities. It can be proved by the stability performance which the maximum value of GZ is at 26.40. The resistance calculation result is indicated that the drag of coefficient of this hull form is about 0.013.

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Kapetanović, Nadir, Jurica Goričanec, Ivo Vatavuk, Ivan Hrabar, Dario Stuhne, Goran Vasiljević, Zdenko Kovačić, et al. "Heterogeneous Autonomous Robotic System in Viticulture and Mariculture: Vehicles Development and Systems Integration." Sensors 22, no. 8 (April 12, 2022): 2961. http://dx.doi.org/10.3390/s22082961.

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There are activities in viticulture and mariculture that require extreme physical endurance from human workers, making them prime candidates for automation and robotization. This paper presents a novel, practical, heterogeneous, autonomous robotic system divided into two main parts, each dealing with respective scenarios in viticulture and mariculture. The robotic components and the subsystems that enable collaboration were developed as part of the ongoing HEKTOR project, and each specific scenario is presented. In viticulture, this includes vineyard surveillance, spraying and suckering with an all-terrain mobile manipulator (ATMM) and a lightweight autonomous aerial robot (LAAR) that can be used in very steep vineyards where other mechanization fails. In mariculture, scenarios include coordinated aerial and subsurface monitoring of fish net pens using the LAAR, an autonomous surface vehicle (ASV), and a remotely operated underwater vehicle (ROV). All robotic components communicate and coordinate their actions through the Robot Operating System (ROS). Field tests demonstrate the great capabilities of the HEKTOR system for the fully autonomous execution of very strenuous and hazardous work in viticulture and mariculture, while meeting the necessary conditions for the required quality and quantity of the work performed.

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Nurhadi, Hendro, Mayga Kiki, Dieky Adzkiya, and Teguh Herlambang. "Estimation of water momentum and propeller velocity in bow thruster model of autonomous surface vehicle using modified Kalman filter." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (December 1, 2022): 5988. http://dx.doi.org/10.11591/ijece.v12i6.pp5988-5997.

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<span lang="EN-US">Autonomous surface vehicle (ASV) is a vehicle in the form of an unmanned on-water surface vessel that can move automatically. As such, an automatic control system is essentially required. The bow thruster system functions as a propulsion control device in its operations. In this research, the water momentum and propeller velocity were estimated based on the dynamic bow thruster model. The estimation methods used is the Kalman filter (KF) and ensemble Kalman filter (EnKF). There are two scenarios: tunnel thruster condition and open-bladed thruster condition. The estimation results in the tunnel thruster condition showed that the root mean square error (RMSE) by the EnKF method was relatively smaller, that is, 0.7920 and 0.1352, while the estimation results in the open-bladed thruster condition showed that the RMSE by the KF method was relatively smaller, that is, 1.9957 and 2.0609.</span>

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Kadhim, Imad Burhan, Ali Najdet Nasret, and Zuhair Shakor Mahmood. "Enhancement and modification of automatic speaker verification by utilizing hidden Markov model." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 3 (September 1, 2022): 1397. http://dx.doi.org/10.11591/ijeecs.v27.i3.pp1397-1403.

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<div class="WordSection1"><p>The purpose of this study is to discuss the design and implementation of autonomous surface vehicle (ASV) systems. There’s a lot riding on the advancement and improvement of ASV applications, especially given the benefits they provide over other biometric approaches. Modern speaker recognition systems rely on statistical models like hidden Markov model (HMM), support vector machine (SVM), artificial neural networks (ANN), generalized method of moments (GMM), and combined models to identify speakers. Using a French dataset, this study investigates the effectiveness of prompted te xt speaker verification. At a context-free, single mixed mono phony level, this study has been constructing a continuous speech system based on HMM. After that, suitable voice data is used to build the client and world models. In order to verify speakers, the text-dependent speaker ver-ification system uses sentence HMM that have been concatenated for the key text. Normalized log-likelihood is determined from client model forced by Viterbi algorithm and world model, in the verification step as the difference between the log-likelihood. At long last, a method for figuring out the verification results is revealed.</p></div>

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Karaki, Ali Alakbar, Marco Bibuli, Massimo Caccia, Ilaria Ferrando, Sara Gagliolo, Angelo Odetti, and Domenico Sguerso. "Multi-Platforms and Multi-Sensors Integrated Survey for the Submerged and Emerged Areas." Journal of Marine Science and Engineering 10, no. 6 (May 30, 2022): 753. http://dx.doi.org/10.3390/jmse10060753.

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In this paper, the state-of-the-art concerning new methodologies for surveying in coastal areas in order to obtain an efficient quantification of submerged and emerged environments is described and evaluated. This work integrates an interdisciplinary approach involving both geomatics and robotics and focuses on definition, implementation, and development of a methodology to execute integrated aerial and underwater survey campaigns in shallow water areas. A preliminary test was performed at Gorzente Lakes near Genoa (Italy), to develop and integrate different survey techniques, enabling working in a smarter way, reducing costs and increasing safety for the operators. In this context, Remote Sensing techniques were integrated with a UAV (Unmanned Aerial Vehicle) carrying an aerial optical sensor for photogrammetry and with an ASV (Autonomous Surface Vehicle) expressly addressed to work in extremely shallow water with underwater acoustic sensors (single echo sounder). The obtained continuous seamless DSM (Digital Surface Model) for the entire environment was reconstructed by the combination of different sensing systems by limiting reliance on the GNSS (Global Navigation Satellite System) support. The obtained DSM was displayed in a 3D model leading to the evaluation of the water flow volume and rendering of 3D visualization.

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Cryer, Sarah, Filipa Carvalho, Terry Wood, James Asa Strong, Peter Brown, Socratis Loucaides, Arlene Young, Richard Sanders, and Claire Evans. "Evaluating the Sensor-Equipped Autonomous Surface Vehicle C-Worker 4 as a Tool for Identifying Coastal Ocean Acidification and Changes in Carbonate Chemistry." Journal of Marine Science and Engineering 8, no. 11 (November 19, 2020): 939. http://dx.doi.org/10.3390/jmse8110939.

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The interface between land and sea is a key environment for biogeochemical carbon cycling, yet these dynamic environments are traditionally under sampled. Logistical limitations have historically precluded a comprehensive understanding of coastal zone processes, including ocean acidification. Using sensors on autonomous platforms is a promising approach to enhance data collection in these environments. Here, we evaluate the use of an autonomous surface vehicle (ASV), the C-Worker 4 (CW4), equipped with pH and pCO2 sensors and with the capacity to mount additional sensors for up to 10 other parameters, for the collection of high-resolution data in shallow coastal environments. We deployed the CW4 on two occasions in Belizean coastal waters for 2.5 and 4 days, demonstrating its capability for high-resolution spatial mapping of surface coastal biogeochemistry. This enabled the characterisation of small-scale variability and the identification of sources of low pH/high pCO2 waters as well as identifying potential controls on coastal pH. We demonstrated the capabilities of the CW4 in both pre-planned “autonomous” mission mode and remote “manually” operated mode. After documenting platform behaviour, we provide recommendations for further usage, such as the ideal mode of operation for better quality pH data, e.g., using constant speed. The CW4 has a high power supply capacity, which permits the deployment of multiple sensors sampling concurrently, a shallow draught, and is highly controllable and manoeuvrable. This makes it a highly suitable tool for observing and characterising the carbonate system alongside identifying potential drivers and controls in shallow coastal regions.

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Peralta, Federico, Daniel Gutierrez Reina, Sergio Toral, Mario Arzamendia, and Derlis Gregor. "A Bayesian Optimization Approach for Multi-Function Estimation for Environmental Monitoring Using an Autonomous Surface Vehicle: Ypacarai Lake Case Study." Electronics 10, no. 8 (April 18, 2021): 963. http://dx.doi.org/10.3390/electronics10080963.

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Bayesian optimization is a sequential method that can optimize a single and costly objective function based on a surrogate model. In this work, we propose a Bayesian optimization system dedicated to monitoring and estimating multiple water quality parameters simultaneously using a single autonomous surface vehicle. The proposed work combines different strategies and methods for this monitoring task, evaluating two approaches for acquisition function fusion: the coupled and the decoupled techniques. We also consider dynamic parametrization of the maximum measurement distance traveled by the ASV so that the monitoring system balances the total number of measurements and the total distance, which is related to the energy required. To evaluate the proposed approach, the Ypacarai Lake (Paraguay) serves as the test scenario, where multiple maps of water quality parameters, such as pH and dissolved oxygen, need to be obtained efficiently. The proposed system is compared with the predictive entropy search for multi-objective optimization with constraints (PESMOC) algorithm and the genetic algorithm (GA) path planning for the Ypacarai Lake scenario. The obtained results show that the proposed approach is 10.82% better than other optimization methods in terms of R2 score with noiseless measurements and up to 17.23% better when the data are noisy. Additionally, the proposed approach achieves a good average computational time for the whole mission when compared with other methods, 3% better than the GA technique and 46.5% better than the PESMOC approach.

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Pereira, Maria Inês, Pedro Nuno Leite, and Andry Maykol Pinto. "A 3-D Lightweight Convolutional Neural Network for Detecting Docking Structures in Cluttered Environments." Marine Technology Society Journal 55, no. 4 (July 1, 2021): 88–98. http://dx.doi.org/10.4031/mtsj.55.4.9.

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Abstract The maritime industry has been following the paradigm shift toward the automation of typically intelligent procedures, with research regarding autonomous surface vehicles (ASVs) having seen an upward trend in recent years. However, this type of vehicle cannot be employed on a full scale until a few challenges are solved. For example, the docking process of an ASV is still a demanding task that currently requires human intervention. This research work proposes a volumetric convolutional neural network (vCNN) for the detection of docking structures from 3-D data, developed according to a balance between precision and speed. Another contribution of this article is a set of synthetically generated data regarding the context of docking structures. The dataset is composed of LiDAR point clouds, stereo images, GPS, and Inertial Measurement Unit (IMU) information. Several robustness tests carried out with different levels of Gaussian noise demonstrated an average accuracy of 93.34% and a deviation of 5.46% for the worst case. Furthermore, the system was fine-tuned and evaluated in a real commercial harbor, achieving an accuracy of over 96%. The developed classifier is able to detect different types of structures and works faster than other state-of-the-art methods that establish their performance in real environments.

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Soofi, Khalid, and Sudhir Pai. "The Use of Autonomous Marine Vehicles by the Hydrocarbon Industry: A Proof of Concept Mission." Marine Technology Society Journal 52, no. 6 (November 1, 2018): 32–38. http://dx.doi.org/10.4031/mtsj.52.6.16.

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AbstractA proof of concept and validation mission was conducted by ConocoPhillips to test the ability of autonomous marine vehicles (AMVs) to (1) collect and validate metocean data, (2) monitor loop and eddy currents, and (3) detect surface oil slicks with accompanying in-situ measurements. During this mission, four AMVs, two equipped with meteorological and oceanographic (METOC) sensors and two equipped with hydrocarbon (SEEP) sensors, were deployed. The METOC vehicles were equipped with Teledyne RDI Workhorse acoustic Doppler current profilers (ADCPs) and were launched to monitor and delineate eddy current features at near-surface depths in the vicinity of the ConocoPhillips asset, Magnolia platform in the Gulf of Mexico. The SEEP vehicles monitored areas identified with natural seep-related hydrocarbon surface expressions. With respect to mission objectives, the sensors were deployed in challenging oceanographic conditions, thus reducing demands on people and large vessels. Mission-based statistics per vehicle were gathered and tabulated capturing the total days at sea (59 days), distance traveled (881.45‐1526.49 nautical miles), and average speed (0.66‐1.08 knots) for validation of AMV as a platform. The mission showed a novel way of using technology that is safe and environmentally friendly and at a lower price point than traditional data acquisition methods. The AMV, hence, provides a substantial competitive advantage to acquiring data in a safe, reliable manner with greater operational efficiencies.

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Fossum, Trygve Olav, John Ryan, Tapan Mukerji, Jo Eidsvik, Thom Maughan, Martin Ludvigsen, and Kanna Rajan. "Compact models for adaptive sampling in marine robotics." International Journal of Robotics Research 39, no. 1 (November 11, 2019): 127–42. http://dx.doi.org/10.1177/0278364919884141.

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Finding high-value locations for in situ data collection is of substantial importance in ocean science, where diverse bio-physical processes interact to create dynamically evolving phenomena. These cover a variable spatial extent, and are sparse and difficult to predict. Autonomous robotic platforms can sustain themselves in harsh conditions with persistent presence, but require deployment at the correct place and time. To that end, we consider the use of remote sensing data for building compact models that can improve skill in predicting sub-mesoscale features and inform onboard sampling. The model enables prediction of regional patterns based on sparse in situ data, a capability that is essential in regions where use of satellite remote sensing in real time is often limited by cloud cover. Our model is based on classification of sea-surface temperature (SST) images, but the technique is general across any remotely sensed parameter. Images having similar magnitude and spatial patterns are grouped into a compact set of conditional means representing the dominant states. The classification is unsupervised and uses a combination of dictionary learning and hierarchical clustering. The method is demonstrated using SST images from Monterey Bay, California. The consistency of the classification result is verified and compared with oceanographic forcing using historical wind measurements. The established model is then shown to work in a real application using measurements from an autonomous surface vehicle (ASV), together with forecast and sampling strategies. Finally an analysis of the model prediction error is presented and compared across different paths and survey duration.

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Molina-Molina, J. Carlos, Marouane Salhaoui, Antonio Guerrero-González, and Mounir Arioua. "Autonomous Marine Robot Based on AI Recognition for Permanent Surveillance in Marine Protected Areas." Sensors 21, no. 8 (April 10, 2021): 2664. http://dx.doi.org/10.3390/s21082664.

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The world’s oceans are one of the most valuable sources of biodiversity and resources on the planet, although there are areas where the marine ecosystem is threatened by human activities. Marine protected areas (MPAs) are distinctive spaces protected by law due to their unique characteristics, such as being the habitat of endangered marine species. Even with this protection, there are still illegal activities such as poaching or anchoring that threaten the survival of different marine species. In this context, we propose an autonomous surface vehicle (ASV) model system for the surveillance of marine areas by detecting and recognizing vessels through artificial intelligence (AI)-based image recognition services, in search of those carrying out illegal activities. Cloud and edge AI computing technologies were used for computer vision. These technologies have proven to be accurate and reliable in detecting shapes and objects for which they have been trained. Azure edge and cloud vision services offer the best option in terms of accuracy for this task. Due to the lack of 4G and 5G coverage in offshore marine environments, it is necessary to use radio links with a coastal base station to ensure communications, which may result in a high response time due to the high latency involved. The analysis of on-board images may not be sufficiently accurate; therefore, we proposed a smart algorithm for autonomy optimization by selecting the proper AI technology according to the current scenario (SAAO) capable of selecting the best AI source for the current scenario in real time, according to the required recognition accuracy or low latency. The SAAO optimizes the execution, efficiency, risk reduction, and results of each stage of the surveillance mission, taking appropriate decisions by selecting either cloud or edge vision models without human intervention.

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Stanghellini, Giuseppe, Camilla Bidini, Claudia Romagnoli, Renata Archetti, Massimo Ponti, Eva Turicchia, Fabrizio Del Bianco, et al. "Repeated (4D) Marine Geophysical Surveys as a Tool for Studying the Coastal Environment and Ground-Truthing Remote-Sensing Observations and Modeling." Remote Sensing 14, no. 22 (November 21, 2022): 5901. http://dx.doi.org/10.3390/rs14225901.

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Sandy beaches and the nearshore environment are dynamic coastal systems characterized by sediment mobilization driven by alternating stormy and mild wave conditions. However, this natural behavior of beaches can be altered by coastal defense structures. Repeated surveys carried out with autonomous surface vehicles (ASVs) may represent an interesting tool for studying nearshore dynamics and testing the effects of mitigation strategies against erosion. We present a one-year experiment involving repeated stratigraphic and morpho-bathymetric surveys of a nearshore environment prone to coastal erosion along the Emilia-Romagna coast (NE Italy), the Lido di Dante beach, carried out between October 2020 and December 2021 using an ASV. Seafloor and subseafloor “snapshots” collected at different time intervals enabled us to delineate the seasonal variability and shed light on key controlling variables, which could be used to integrate and calibrate remote-sensing observations and modeling. The results demonstrated that repeated surveys could be successfully employed for monitoring coastal areas and represent a promising tool for studying coastal dynamics on a medium/short (years/months) timescale.

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Hong, Xiaobin, Liuwei Huang, Shifeng Gong, and Guoquan Xiao. "Shedding Damage Detection of Metal Underwater Pipeline External Anticorrosive Coating by Ultrasonic Imaging Based on HOG + SVM." Journal of Marine Science and Engineering 9, no. 4 (March 29, 2021): 364. http://dx.doi.org/10.3390/jmse9040364.

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Underwater pipelines are the channels for oil transportation in the sea. In the course of pipeline operation, leakage accidents occur from time to time for natural and man-made reasons which result in economic losses and environmental pollution. To avoid economic losses and environmental pollution, damage detection of underwater pipelines must be carried out. In this paper, based on the histogram of oriented gradient (HOG) and support vector machine (SVM), a non-contact ultrasonic imaging method is proposed to detect the shedding damage of the metal underwater pipeline external anti-corrosion layer. Firstly, the principle of acoustic scattering characteristics for detecting the metal underwater pipelines is introduced. Following this, a HOG+SVM image-extracting algorithm is used to extract the pipeline area from the underwater ultrasonic image. According to the difference of mean gray value in the horizontal direction of the pipeline project area, the shedding damage parts are identified. Subsequently, taking the metal underwater pipelines with three layers of polyethylene outer anti-corrosive coatings as the detection object, an Autonomous Surface Vehicle (ASV) for underwater pipelines defect detection is developed to verify the detection effect of the method. Finally, the underwater ultrasonic image which used to detect the metal underwater pipeline shedding damage is obtained by acoustic sensor. The results show that the shedding damage can be detected by the proposed method. With the increase of shedding damage width, the effect of pipeline defect location detection is better.

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Sproles, Eric A., Andrew Mullen, Jordy Hendrikx, Charles Gatebe, and Suzi Taylor. "Autonomous Aerial Vehicles (AAVs) as a Tool for Improving the Spatial Resolution of Snow Albedo Measurements in Mountainous Regions." Hydrology 7, no. 3 (July 15, 2020): 41. http://dx.doi.org/10.3390/hydrology7030041.

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We present technical advances and methods to measure effective broadband physical albedo in snowy mountain headwaters using a prototype dual-sensor pyranometer mounted on an Autonomous Aerial Vehicle (an AAV). Our test flights over snowy meadows and forested areas performed well during both clear sky and snowy/windy conditions at an elevation of ~2650 m above mean sea level (MSL). Our AAV-pyranometer platform provided high spatial (m) and temporal resolution (sec) measurements of effective broadband (310–2700 nm) surface albedo. The AAV-based measurements reveal spatially explicit changes in landscape albedo that are not present in concurrent satellite measurements from Landsat and MODIS due to a higher spatial resolution. This AAV capability is needed for validation of satellite snow albedo products, especially over variable montane landscapes at spatial scales of critical importance to hydrological applications. Effectively measuring albedo is important, as annually the seasonal accumulation and melt of mountain snowpack represent a dramatic transformation of Earth’s albedo, which directly affects headwaters’ water and energy cycles.

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Duarte, Diogo Ferreira, Maria Inês Pereira, and Andry Maykol Pinto. "Multiple Vessel Detection in Harsh Maritime Environments." Marine Technology Society Journal 56, no. 5 (October 14, 2022): 58–67. http://dx.doi.org/10.4031/mtsj.56.5.07.

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Abstract Recently, research concerning the navigation of autonomous surface vehicles (ASVs) has been increasing. However, a large-scale implementation of these vessels is still held back by several challenges such as multi-object tracking. Attaining accurate object detection plays a big role in achieving successful tracking. This article presents the development of a detection model with an image-based Convolutional Neural Network trained through transfer learning, a deep learning technique. To train, test, and validate the detector module, data were collected with the SENSE ASV by sailing through two nearby ports, Leixões and Viana do Castelo, and recording video frames through its on-board cameras, along with a Light Detection And Ranging, GPS, and Inertial Measurement Unit data. Images were extracted from the collected data, composing a manually annotated dataset with nine classes of different vessels, along with data from other open-source maritime datasets. The developed model achieved a class mAP@[.5 .95] (mean average precision) of 89.5% and a clear improvement in boat detection compared to a multi-purposed state-of-the-art detector, YOLO-v4, with a 22.9% and 44.3% increase in the mAP with an Intersection over Union threshold of 50% and the mAP@[.5 .95], respectively. It was integrated in a detection and tracking system, being able to continuously detect nearby vessels and provide sufficient information for simple navigation tasks.

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Journal articles on the topic 'Autonomous surface vehicle (ASV)'

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