Relevant bibliographies by topics / Autonomous Transformable Marine Robot

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Autonomous Transformable Marine Robot'

Author: Grafiati
Published: 10 March 2023

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Journal articles on the topic "Autonomous Transformable Marine Robot"

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Woolley, Robert, Jon Timmis, and Andy M. Tyrrell. "Cylindabot: Transformable Wheg Robot Traversing Stepped and Sloped Environments." Robotics 10, no. 3 (August 30, 2021): 104. http://dx.doi.org/10.3390/robotics10030104.

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The ability of an autonomous robot to adapt to different terrain affords the flexibility to move successfully in a range of environments. This paper proposes the Cylindabot, a transformable Wheg robot that can move with two large wheels, each of which can rotate out, producing three legs. This ability to change its mode of locomotion allows for specialised performance. The Cylindabot has been tested in simulation and on a physical robot on steps and slopes as an indication of its efficacy in different environments. These experiments show that such robots are capable of climbing up to a 32 degree slope and a step 1.43 times their initial height. Theoretical limits are devised that match the results, and a comparison with existing Wheg platforms is made.
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Kim, Hyun-Sik, Hyung-Joo Kang, Youn-Jae Ham, and Seung-Soo Park. "Development of Underwater-type Autonomous Marine Robot-kit." Journal of Korean Institute of Intelligent Systems 22, no. 3 (June 25, 2012): 312–18. http://dx.doi.org/10.5391/jkiis.2012.22.3.312.

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Jeong, Jinseok, Youngmin Sa, and Hyun-Sik Kim. "Development of Autonomous Surface Robot for Marine Fire Safety." Journal of Ocean Engineering and Technology 32, no. 2 (April 30, 2018): 138–42. http://dx.doi.org/10.26748/ksoe.2018.4.32.2.138.

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Gurenko, Boris, Roman Fedorenko, Maksim Beresnev, and Roman Saprykin. "Development of Simulator for Intelligent Autonomous Underwater Vehicle." Applied Mechanics and Materials 799-800 (October 2015): 1001–5. http://dx.doi.org/10.4028/www.scientific.net/amm.799-800.1001.

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Testing and debugging of real equipment is a time consuming task. In particular, in the case of marine robots, it is necessary each time to carry out the transportation and deployment of a robot on the water. Experiments with not yet fully functional prototype of marine robot equipped with expensive hardware is in the meantime very risky. Therefore, the use of simulators is affordable way to accelerate the development of robotic systems from the viewpoint of labor effort and cost of experiments. This paper presents a simulator specifically designed for autonomous unmanned underwater vehicles.
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Anto, Adhy Febry, and Totok Sukardiyono. "Prototype Autonomous Rover Pembersih Sampah Pantai menggunakan ArduPilot." Elinvo (Electronics, Informatics, and Vocational Education) 4, no. 2 (December 13, 2019): 202–9. http://dx.doi.org/10.21831/elinvo.v4i2.28793.

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Indonesia has the second longest coastline in the world. On the other hand, Indonesia is the second largest contributor to marine waste in the world. Coastal cleanliness needs to be maintained so that it becomes an attraction for tourism and to protect the marine ecosystem. This article describes the results of testing devices that can be used to clean beaches. Research carried out by the development method. An autonomous beach garbage cleaning rover is a beach trash sweeper robot equipped with GPS, compass, telemetry, ArduPilot as a navigation and communication system when the robot operates. This robot moves using 2 DC motors with torque of ± 4 kg. The robot is also equipped with a conveyor that functions to sweep plastic debris on the beach. The test results show that the robot can go according to the specified path, according to the coordinates entered (100% accuracy) and be able to transport plastic waste. This is because the motor used has a small torque, so it is not able to lift large objects. The next robot development can be done in terms of: identifying the capacity of robots to accommodate various types of waste, testing the ability of robots to clean waste, the use of solar cells, and trajectory management systems.
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Bonin-Font, Francisco, and Antoni Burguera. "Towards Multi-Robot Visual Graph-SLAM for Autonomous Marine Vehicles." Journal of Marine Science and Engineering 8, no. 6 (June 14, 2020): 437. http://dx.doi.org/10.3390/jmse8060437.

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State of the art approaches to Multi-robot localization and mapping still present multiple issues to be improved, offering a wide range of possibilities for researchers and technology. This paper presents a new algorithm for visual Multi-robot simultaneous localization and mapping, used to join, in a common reference system, several trajectories of different robots that participate simultaneously in a common mission. One of the main problems in centralized configurations, where the leader can receive multiple data from the rest of robots, is the limited communications bandwidth that delays the data transmission and can be overloaded quickly, restricting the reactive actions. This paper presents a new approach to Multi-robot visual graph Simultaneous Localization and Mapping (SLAM) that aims to perform a joined topological map, which evolves in different directions according to the different trajectories of the different robots. The main contributions of this new strategy are centered on: (a) reducing to hashes of small dimensions the visual data to be exchanged among all agents, diminishing, in consequence, the data delivery time, (b) running two different phases of SLAM, intra- and inter-session, with their respective loop-closing tasks, with a trajectory joining action in between, with high flexibility in their combination, (c) simplifying the complete SLAM process, in concept and implementation, and addressing it to correct the trajectory of several robots, initially and continuously estimated by means of a visual odometer, and (d) executing the process online, in order to assure a successful accomplishment of the mission, with the planned trajectories and at the planned points. Primary results included in this paper show a promising performance of the algorithm in visual datasets obtained in different points on the coast of the Balearic Islands, either by divers or by an Autonomous Underwater Vehicle (AUV) equipped with cameras.
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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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Mellinger, David K., Holger Klinck, Neil M. Bogue, Jim Luby, Haru Matsumoto, and Roland Stelzer. "Gliders, floats, and robot sailboats: autonomous platforms for marine mammal research." Journal of the Acoustical Society of America 131, no. 4 (April 2012): 3493. http://dx.doi.org/10.1121/1.4709197.

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Pan, Lisheng. "Exploration and Mining Learning Robot of Autonomous Marine Resources Based on Adaptive Neural Network Controller." Polish Maritime Research 25, s3 (December 1, 2018): 78–83. http://dx.doi.org/10.2478/pomr-2018-0115.

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Abstract To study the autonomous learning model of the learning robot for marine resource exploration, an adaptive neural network controller was applied. The motion characteristics of autonomous learning robots were identified. The mathematical model of the multilayer forward neural network and its improved learning algorithm were studied. The improved Elman regression neural network and the composite input dynamic regression neural network were further discussed. At the same time, the diagonal neural network was analysed from the structure and learning algorithms. The results showed that for the complex environment of the ocean, the structure of the composite input dynamic regression network was simple, and the convergence was fast. In summary, the identification method of underwater robot system based on neural network is effective.
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Ahmed, Mohammed, Markus Eich, and Felix Bernhard. "Design and Control of MIRA: A Lightweight Climbing Robot for Ship Inspection." International Letters of Chemistry, Physics and Astronomy 55 (July 2015): 128–35. http://dx.doi.org/10.18052/www.scipress.com/ilcpa.55.128.

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The inspection of marine vessels is currently per-formed manually. Inspectors use tools (e.g. cameras and devices for non-destructive testing) to detect damaged areas, cracks, and corrosion in large cargo holds, tanks, and other parts of a ship. Due to the size and complex geometry of most ships, ship inspection is time-consuming and expensive. The EU-funded project INCASS develops concepts for a marine inspection robotic assistant system to improve and automate ship inspections. In this paper, we introduce our magnetic wall–climbing robot: Marine Inspection Robotic Assistant (MIRA). This semi-autonomous lightweight system is able to climb a vessels steel frame to deliver on-line visual inspection data. In addition, we describe the design of the robot and its building subsystems as well as its hardware and software components.
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Dissertations / Theses on the topic "Autonomous Transformable Marine Robot"

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Bazeille, Stéphane. "Vision sous-marine monoculaire pour la reconnaissance d'objets." Brest, 2008. http://www.theses.fr/2008BRES2023.

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Dans le contexte sous-marin, et à l’inverse du capteur sonar qui reste le plus employé à grande distance pour la détection et la classification, la caméra vidéo est efficace à faible portée lors des phases d’approche, de reconnaissance d’objets et d’intervention. Elle dispose en effet d’atouts notables comme une haute résolution, une facilité d’interprétation on encore un faible coût. Aujourd’hui presque tous les véhicules sous-marins scientifiques, industriels ou militaires en sont équipés. Ils sont actuellement plutôt télé-opérés par un opérateur et on y trouve associés des traitements automatiques que très rarement. Ces traitements automatiques sont pourtant des technologies essentielles pour les développements émergents des robots autonomes sous-marins très prisés aujourd’hui dans un contexte d’expansion des marchés liés à la sécurité et à l’exploitation des ressources maritimes. Ces travaux de thèse visent à apporter les innovations nécessaires, et à promouvoir l’emploi du capteur vidéo dans le domaine sous-marin. L’étude proposée concerne le développement des traitements automatiques de reconnaissance d’objets en vidéo sous-marine, avec une attention particulière apportée aux objets manufacturés. Les scènes sous-marines observées sont classiquement plus simples et plus limitées en profondeur d’observation que les scènes urbaines ou que l’intérieur d’un bâtiment. Toutefois, ce contexte présente des difficultés spécifiques telles que les variations d’éclairage et la turbidité de l’eau qui limitent la visibilité et dégradent fortement les images. Ceci a pour conséquence de rendre les traitements difficiles et nécessite donc la création de nouveaux algorithmes de vision robotique
In underwater context, traditional sensing methods like sonar are used at large range for detection and classification of objects. For a few years, the sonar sensor has been complemented by a vision sensor more efficient at short range for the approach, the object recognition and the intervention phases. Indeed, the camera has noticeable advantages like for example high resolution, simple interpretation or low cost. Today, it equips nearly any scientific, industrial or military underwater vehicles. Currently, underwater vehicles are rather distance controlled by a manipulator, and automatic processing is really uncommon. However, automatic processing is an essential technology for the AUV development. These kinds of vehicles are very popular today with the expansion of the market related to the security and the exploitation of the marine resources. This thesis aims at supplying the required advances and promoting the use of video technologies. The proposed study addresses the problem of automatic processing for underwater objects recognition, with a particular focus on man-made objects. Observed underwater scenes are traditionally simpler but more limited in depth than urban scenes or inside building scenes. Nevertheless, this context presents very specific difficulties like lighting variations and water turbidity which limit visibility and degrade considerably images. As a consequence processing is difflcult and require the development of new robotic vision algorithms
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Pagliai, Marco. "Design and testing of innovative thrusters and their integration in the design of a reconfigurable underwater vehicle." Doctoral thesis, 2019. http://hdl.handle.net/2158/1154277.

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Nowadays, Unmanned Underwater Vehicles (UUVs) are increasingly used in underwater operations (e.g. exploration, monitoring, maintenance), because they make safe working under the water. Since their use is growing, it is extremely important to ensure better maneuverability and lower power consumption to improve the performances of this kind of vehicles. The work carried out in the last three years at the Mechatronics and Dynamic Modelling Laboratory (MDM Lab) of the Department of Industrial Engineering of University of Florence (UNIFI DIEF), focused exactly on these problematics. More in details, the study presented below concerned both an in-depth analysis of current commercial and research UUVs, with the aim to define the specifications and the design of a new type of underwater vehicle, and the study of commercial low cost motors, with the purpose of improving their performance thus the one of the mobile robots they are mounted on. In the introduction a short summary of the UUVs history is reported and all the vehicle of UNIFI DIEF are presented. In the first chapter, instead, a deep analysis of the state of art of underwater vehicles is reported. This study has been divided into AUVs (Autonomous Underwater Vehicles), ROVs (Remotely Operated Vehicle) and Gliders features, taking into account especially their propulsion systems. In addition, based on also the study of the state of art, the conceptual design of an innovative vehicle capable of changing its shape and its thrusters layout is synthetized. In the following chapter (chapter 2), the design of the innovative vehicle is described, in order to verify the feasibility of the vehicle itself exploiting current technology and to estimate its performances and the budget required for its realization. In chapter 3, a low cost commercial thruster is presented. With these thrusters all the vehicles of UNIFI DIEF have been equipped; for this reason, the third chapter reports a deep experimental study to define the relation between thruster parameters and the input command. This study has been very important because it allows improving the thruster parameters estimation and consequently the control performances. In addition, in this third chapter the new vehicle designed by UNIFI DIEF with the collaboration of MDM Team s.r.l. (an University of Florence Spin Off) and named ZENO is presented. In chapter 4, it is shown how the thruster studied in the previous chapter has been upgraded and hardware modifications have been made. More in details, in this chapter it is explained how a Hall effect sensor has been integrated in the thruster in order to measure the rotor speed. In addition, it is shown how a low cost closed loop control system has been implemented for the thruster previously described and the results obtained on dedicated test rig are given. Finally, in the conclusion the results obtained are summarized, highlighting how the designed innovative vehicle is feasible and has the performances required by its hypothetical application. In addition, it is summarized how the studied thrusters have improved the UNIFI DIEF vehicles performances.
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"Coordinated Navigation and Localization of an Autonomous Underwater Vehicle Using an Autonomous Surface Vehicle in the OpenUAV Simulation Framework." Master's thesis, 2020. http://hdl.handle.net/2286/R.I.62789.

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abstract: The need for incorporating game engines into robotics tools becomes increasingly crucial as their graphics continue to become more photorealistic. This thesis presents a simulation framework, referred to as OpenUAV, that addresses cloud simulation and photorealism challenges in academic and research goals. In this work, OpenUAV is used to create a simulation of an autonomous underwater vehicle (AUV) closely following a moving autonomous surface vehicle (ASV) in an underwater coral reef environment. It incorporates the Unity3D game engine and the robotics software Gazebo to take advantage of Unity3D's perception and Gazebo's physics simulation. The software is developed as a containerized solution that is deployable on cloud and on-premise systems. This method of utilizing Gazebo's physics and Unity3D perception is evaluated for a team of marine vehicles (an AUV and an ASV) in a coral reef environment. A coordinated navigation and localization module is presented that allows the AUV to follow the path of the ASV. A fiducial marker underneath the ASV facilitates pose estimation of the AUV, and the pose estimates are filtered using the known dynamical system model of both vehicles for better localization. This thesis also investigates different fiducial markers and their detection rates in this Unity3D underwater environment. The limitations and capabilities of this Unity3D perception and Gazebo physics approach are examined.
Dissertation/Thesis
Masters Thesis Computer Science 2020
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Lu, Yimeng. "A Game-theoretical Approach for Distributed Cooperative Control of Autonomous Underwater Vehicles." Thesis, 2018. http://hdl.handle.net/10754/627955.

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This thesis explores a game-theoretical approach for underwater environmental monitoring applications. We first apply game-theoretical algorithm to multi-agent resource coverage problem in drifting environments. Furthermore, existing utility design and learning process of the algorithm are modified to fit specific constraints of underwater exploration/monitoring tasks. The revised approach can take the real scenario of underwater monitoring applications such as the effect of sea current, previous knowledge of the resource and occasional communications between agents into account, and adapt to them to reach better performance. As the motivation of this thesis is from real applications, in this work we emphasize highly on implementation phase. A ROS-Gazebo simulation environment was created for preparation of actual tests. The algorithms are implemented in simulating both the dynamics of vehicles and the environment. After that, a multi-agent underwater autonomous robotic system was developed for hardware test in real settings with local controllers to make their own decisions. These systems are used for testing above mentioned algorithms and future development of other underwater projects. After that, other works related to robotics during this thesis will be briefly mentioned, including contributions in MBZIRC robotics competition and distributed control of UAVs in an adversarial environment.
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Books on the topic "Autonomous Transformable Marine Robot"

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Marine Robot Autonomy. Springer, 2012.

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Book chapters on the topic "Autonomous Transformable Marine Robot"

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Paull, Liam, Sajad Saeedi, and Howard Li. "Path Planning for Autonomous Underwater Vehicles." In Marine Robot Autonomy, 177–223. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5659-9_4.

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Lane, David, Keith Brown, Yvan Petillot, Emilio Miguelanez, and Pedro Patron. "An Ontology-Based Approach to Fault Tolerant Mission Execution for Autonomous Platforms." In Marine Robot Autonomy, 225–55. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5659-9_5.

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Novitzky, Michael, Hugh R. R. Dougherty, and Michael R. Benjamin. "A Human-Robot Speech Interface for an Autonomous Marine Teammate." In Social Robotics, 513–20. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47437-3_50.

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Valada, A., P. Velagapudi, B. Kannan, C. Tomaszewski, G. Kantor, and P. Scerri. "Development of a Low Cost Multi-Robot Autonomous Marine Surface Platform." In Springer Tracts in Advanced Robotics, 643–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40686-7_43.

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Schmitt, Silke, Fabrice Le Bars, Luc Jaulin, and Thomas Latzel. "Obstacle Avoidance for an Autonomous Marine Robot—A Vector Field Approach." In Quantitative Monitoring of the Underwater Environment, 119–31. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32107-3_11.

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Choyekh, Mahdi, Naomi Kato, Yasuaki Yamaguchi, Ryan Dewantara, Hajime Chiba, Hidetaka Senga, Muneo Yoshie, Toshinari Tanaka, Eiichi Kobayashi, and Timothy Short. "Development and Operation of Underwater Robot for Autonomous Tracking and Monitoring of Subsea Plumes After Oil Spill and Gas Leak from Seabed and Analyses of Measured Data." In Applications to Marine Disaster Prevention, 17–93. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-55991-7_3.

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Kapetanović, Nadir, Antonio Vasilijević, and Krunoslav Zubčić. "Assessing the Current State of a Shipwreck Using an Autonomous Marine Robot: Szent Istvan Case Study." In Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference, 126–35. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53829-3_12.

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Conference papers on the topic "Autonomous Transformable Marine Robot"

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Maurelli, Francesco, Zeyn Saigol, Carlos C. Insaurralde, Yvan R. Petillot, and David M. Lane. "Marine world representation and acoustic communication: Challenges for multi-robot collaboration." In 2012 IEEE/OES Autonomous Underwater Vehicles (AUV). IEEE, 2012. http://dx.doi.org/10.1109/auv.2012.6380755.

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Han, Changlin, Yiyao Xu, Xiaohong Xu, Zhiwen Zeng, Huimin Lu, and Zongtan Zhou. "Remote Control and Autonomous Driving: The System-wide Design of a Wheel-track Transformable Robot –– Kylin Blaster." In 2018 Chinese Automation Congress (CAC). IEEE, 2018. http://dx.doi.org/10.1109/cac.2018.8623389.

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Kiselev, L. V., A. V. Medvedev, V. B. Kostousov, and A. E. Tarkhanov. "Autonomous underwater robot as an ideal platform for marine gravity surveys." In 2017 24th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS). IEEE, 2017. http://dx.doi.org/10.23919/icins.2017.7995685.

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Soares, Ines, Sara Sa, Joao Morais, and Joao Fortuna. "Obstacle Avoiding Path Planning Pipeline for Marine Surface Vessels." In 2022 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2022. http://dx.doi.org/10.1109/icarsc55462.2022.9784810.

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"Exploring the Blue Frontier with Cooperative Marine Robots: Theory and Practice." In 2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2020. http://dx.doi.org/10.1109/icarsc49921.2020.9096122.

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Ueland, Einar S., Roger Skjetne, and Andreas R. Dahl. "Marine Autonomous Exploration Using a Lidar and SLAM." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61880.

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This paper presents the implementation of a 2D-lidar to a model-scale surface vessel, and the design of a control system that makes the vessel able to perform autonomous exploration of a small-scale marine environment by the use of the lidar and SLAM. This includes a presentation and discussion of experimental results. The completion of this system has involved the development of a suitable control system that merges exploration strategies, path planners, a motion controller, and a strategy for generating controller setpoints. The system was implemented on the Robot Operating System platform, which made it possible to utilize open-source algorithms for state of the art SLAM.
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Manderson, Travis, and Gregory Dudek. "GPU-Assisted Learning on an Autonomous Marine Robot for Vision-Based Navigation and Image Understanding." In OCEANS 2018 MTS/IEEE Charleston. IEEE, 2018. http://dx.doi.org/10.1109/oceans.2018.8604645.

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Bennett, Andrew, Victoria Preston, Jay Woo, Shivali Chandra, Devynn Diggins, Riley Chapman, Zhecan Wang, et al. "Autonomous vehicles for remote sample collection in difficult conditions: Enabling remote sample collection by marine biologists." In 2015 IEEE International Conference on Technologies for Practical robot Applications (TePRA). IEEE, 2015. http://dx.doi.org/10.1109/tepra.2015.7219660.

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Zhang, Peihao, Jiawang Chen, Zhenwei Tian, ZiQiang Ren, Yongqiang Ge, Qiaoling Gao, and Feng Gao. "A New Type of Robot Used for Deep Stratum Drilling in Seabed." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-18401.

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Abstract With the increasing scale of the exploitation of ocean oil and gas resources, the decomposition of natural gas hydrate and the exploitation of submarine oil will damage the engineering mechanical structure of submarine sediments, leading to submarine collapse, landslide, even earthquake and other geological disasters, seriously threatening the exploration and exploitation of Marine resources. Therefore, it is necessary to develop a deep-seabed drilling robot to carry out real-time long-term monitoring of changes in the seabed environment by carrying sensors and detection devices. This paper will describe the design structure of the drilling robot, and explain the working process through that the drilling robot is released from the sea bed into the stratum of the mining area, and can achieve autonomous drilling and steering functions in the seabed stratum. In this paper, theoretical analysis and simulation verification will prove the feasibility of the robot moving in the stratum.
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Reports on the topic "Autonomous Transformable Marine Robot"

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Barbie, Alexander. ARCHES Digital Twin Framework. GEOMAR, December 2022. http://dx.doi.org/10.3289/sw_arches_core_1.0.0.

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In the Helmholtz Future Project ARCHES (Autonomous Robotic Networks to Help Modern Societies) with a consortium of partners from AWI (Alfred- Wegener-Institute Helmholtz Centre for Polar and Marine Research), DLR (German Aerospace Center), KIT (Karlsruhe Institute of Technology), and the GEOMAR (Helmholtz Centre for Ocean Research Kiel), several Digital Twins of ocean observation systems were developed by the GEOMAR and AWI. The ARCHES Digital Twin Framework is one of the results of this project. The software is based on the Robot Operating System (ROS) and is written in Python.
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