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Robotics
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Underwater Robotics
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Underwater Robotics

A special issue of Robotics (ISSN 2218-6581).

Deadline for manuscript submissions: closed (15 November 2015) | Viewed by 45282

Special Issue Editors

Prof. Dr. Ingrid Schjølberg

E-Mail Website
Guest Editor
Department of Marine Technology, Norwegian University of Science and Technology, 7491 Trondheim, Norway
Interests: mathematical modelling and control; machine learning; safety and risk management; human–machine interaction; systems integration; industrial robotics; underwater robotics
Prof. Dr. Thor I. Fossen

E-Mail Website
Co-Guest Editor
Department of Engineering Cybernetics, Norwegian University of Science and Technology, 7491 Trondheim, Norway
Interests: guidance; navigation; nonlinear control theory; nonlinear observers; autonomous and intelligent systems; vehicle dynamics; hydrodynamics; vehicle simulators; marine craft and unmanned vehicles (UAV, AUV, USV); autopilots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Underwater robotics is the key technology in future ocean exploration and utilization. Subsea oil and gas factories, exposed aquaculture and deep sea mining are currently the main drivers for development in underwater robotics. There is a need to increase the level of autonomy and reduce the dependency on surface support for cost efficient underwater operations. Moreover, there is an increased demand for sensors and sensor platforms for ocean mapping and monitoring. Development in ICT and materials enable the development of smarter underwater robotic systems. High-level planning/re-planning and reconfiguration of systems subject to a particular mission, robustness to extreme environmental conditions, energy supply, communication constraints, and risk management are key challenges.  Real-time sensor fusion associated with intelligent control task execution, combining one or several sensors for identification, localisation and perception in an uncertain or unknown environment is also a challenge.

This Special Issue will present advances in underwater robotics, and provide a comprehensive overview of future solutions from various computational and engineering aspects. Topics of interest include, but are not limited to, underwater localization, multi-sensor fusion, SLAM, navigation and guidance, fault-tolerant robot control, autonomy, AI, human–machine interaction, safety and risk management and real-world applications of underwater robotic systems.

Prof. Dr. Ingrid Schjølberg
Prof. Dr. Thor I. Fossen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Robotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


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Published Papers (5 papers)

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1812 KiB  
Article
Sensor Fusion and Autonomy as a Powerful Combination for Biological Assessment in the Marine Environment
by Mark A. Moline and Kelly Benoit-Bird
Robotics 2016, 5(1), 4; https://doi.org/10.3390/robotics5010004 - 1 Feb 2016
Cited by 10 | Viewed by 10908
Abstract
The ocean environment and the physical and biological processes that govern dynamics are complex. Sampling the ocean to better understand these processes is difficult given the temporal and spatial domains and sampling tools available. Biological systems are especially difficult as organisms possess behavior, [...] Read more.
The ocean environment and the physical and biological processes that govern dynamics are complex. Sampling the ocean to better understand these processes is difficult given the temporal and spatial domains and sampling tools available. Biological systems are especially difficult as organisms possess behavior, operate at horizontal scales smaller than traditional shipboard sampling allows, and are often disturbed by the sampling platforms themselves. Sensors that measure biological processes have also generally not kept pace with the development of physical counterparts as their requirements are as complex as the target organisms. Here, we attempt to address this challenge by advocating the need for sensor-platform combinations to integrate and process data in real-time and develop data products that are useful in increasing sampling efficiencies. Too often, the data of interest is only garnered after post-processing after a sampling effort and the opportunity to use that information to guide sampling is lost. Here we demonstrate a new autonomous platform, where data are collected, analyzed, and data products are output in real-time to inform autonomous decision-making. This integrated capability allows for enhanced and informed sampling towards improving our understanding of the marine environment. Full article
(This article belongs to the Special Issue Underwater Robotics)
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7749 KiB  
Article
Coordination of Multiple Biomimetic Autonomous Underwater Vehicles Using Strategies Based on the Schooling Behaviour of Fish
by Jonathan McColgan and Euan W. McGookin
Robotics 2016, 5(1), 2; https://doi.org/10.3390/robotics5010002 - 13 Jan 2016
Cited by 12 | Viewed by 8895
Abstract
Biomimetic Autonomous Underwater Vehicles (BAUVs) are Autonomous Underwater Vehicles (AUVs) that employ similar propulsion and steering principles as real fish. While the real life applicability of these vehicles has yet to be fully investigated, laboratory investigations have demonstrated that at low speeds, the [...] Read more.
Biomimetic Autonomous Underwater Vehicles (BAUVs) are Autonomous Underwater Vehicles (AUVs) that employ similar propulsion and steering principles as real fish. While the real life applicability of these vehicles has yet to be fully investigated, laboratory investigations have demonstrated that at low speeds, the propulsive mechanism of these vehicles is more efficient when compared with propeller based AUVs. Furthermore, these vehicles have also demonstrated superior manoeuvrability characteristics when compared with conventional AUVs and Underwater Glider Systems (UGSs). Further performance benefits can be achieved through coordination of multiple BAUVs swimming in formation. In this study, the coordination strategy is based on the schooling behaviour of fish, which is a decentralized approach that allows multiple AUVs to be self-organizing. Such a strategy can be effectively utilized for large spatiotemporal data collection for oceanic monitoring and surveillance purposes. A validated mathematical model of the BAUV developed at the University of Glasgow, RoboSalmon, is used to represent the agents within a school formation. The performance of the coordination algorithm is assessed through simulation where system identification techniques are employed to improve simulation run time while ensuring accuracy is maintained. The simulation results demonstrate the effectiveness of implementing coordination algorithms based on the behavioural mechanisms of fish to allow a group of BAUVs to be considered self-organizing. Full article
(This article belongs to the Special Issue Underwater Robotics)
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1573 KiB  
Article
Robust Design of Docking Hoop for Recovery of Autonomous Underwater Vehicle with Experimental Results
by Wei Peng Lin, Cheng Siong Chin, Leonard Chin Wai Looi, Jun Jie Lim and Elvin Min Ee Teh
Robotics 2015, 4(4), 492-515; https://doi.org/10.3390/robotics4040492 - 1 Dec 2015
Cited by 7 | Viewed by 9484
Abstract
Control systems prototyping is usually constrained by model complexity, embedded system configurations, and interface testing. The proposed control system prototyping of a remotely-operated vehicle (ROV) with a docking hoop (DH) to recover an autonomous underwater vehicle (AUV) named AUVDH using a combination of [...] Read more.
Control systems prototyping is usually constrained by model complexity, embedded system configurations, and interface testing. The proposed control system prototyping of a remotely-operated vehicle (ROV) with a docking hoop (DH) to recover an autonomous underwater vehicle (AUV) named AUVDH using a combination of software tools allows the prototyping process to be unified. This process provides systematic design from mechanical, hydrodynamics, dynamics modelling, control system design, and simulation to testing in water. As shown in a three-dimensional simulation of an AUVDH model using MATLAB™/Simulink™ during the launch and recovery process, the control simulation of a sliding mode controller is able to control the positions and velocities under the external wave, current, and tether forces. In the water test using the proposed Python-based GUI platform, it shows that the AUVDH is capable to perform station-keeping under the external disturbances. Full article
(This article belongs to the Special Issue Underwater Robotics)
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1270 KiB  
Article
Performance of Very Small Robotic Fish Equipped with CMOS Camera
by Yang Zhao, Masaaki Fukuhara, Takahiro Usami and Yogo Takada
Robotics 2015, 4(4), 421-434; https://doi.org/10.3390/robotics4040421 - 22 Oct 2015
Cited by 6 | Viewed by 8833
Abstract
Underwater robots are often used to investigate marine animals. Ideally, such robots should be in the shape of fish so that they can easily go unnoticed by aquatic animals. In addition, lacking a screw propeller, a robotic fish would be less likely to [...] Read more.
Underwater robots are often used to investigate marine animals. Ideally, such robots should be in the shape of fish so that they can easily go unnoticed by aquatic animals. In addition, lacking a screw propeller, a robotic fish would be less likely to become entangled in algae and other plants. However, although such robots have been developed, their swimming speed is significantly lower than that of real fish. Since to carry out a survey of actual fish a robotic fish would be required to follow them, it is necessary to improve the performance of the propulsion system. In the present study, a small robotic fish (SAPPA) was manufactured and its propulsive performance was evaluated. SAPPA was developed to swim in bodies of freshwater such as rivers, and was equipped with a small CMOS camera with a wide-angle lens in order to photograph live fish. The maximum swimming speed of the robot was determined to be 111 mm/s, and its turning radius was 125 mm. Its power consumption was as low as 1.82 W. During trials, SAPPA succeeded in recognizing a goldfish and capturing an image of it using its CMOS camera. Full article
(This article belongs to the Special Issue Underwater Robotics)
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Other

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730 KiB  
Conference Report
Planning the Minimum Time and Optimal Survey Trajectory for Autonomous Underwater Vehicles in Uncertain Current
by Michael A. Hurni and Kiriakos Kiriakidis
Robotics 2015, 4(4), 516-528; https://doi.org/10.3390/robotics4040516 - 16 Dec 2015
Cited by 1 | Viewed by 5640
Abstract
The authors develop an approach to a “best” time path for Autonomous Underwater Vehicles conducting oceanographic measurements under uncertain current flows. The numerical optimization tool DIDO is used to compute hybrid minimum time and optimal survey paths for a sample of currents between [...] Read more.
The authors develop an approach to a “best” time path for Autonomous Underwater Vehicles conducting oceanographic measurements under uncertain current flows. The numerical optimization tool DIDO is used to compute hybrid minimum time and optimal survey paths for a sample of currents between ebb and flow. A simulated meta-experiment is performed where the vehicle traverses the resulting paths under different current strengths per run. The fastest elapsed time emerges from a payoff table. A multi-objective function is then used to weigh the time to complete a mission versus measurement inaccuracy due to deviation from the desired survey path. Full article
(This article belongs to the Special Issue Underwater Robotics)
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