Review on auto-depth control system for an unmanned underwater remotely operated vehicle (ROV) using intelligent controller

This paper presents a review of auto-depth control system for an Unmanned Underwater Remotely operated Vehicle (ROV), focusing on the Artificial Intelligent Controller Techniques. Specifically, Fuzzy Logic Controller (FLC) is utilized in auto-depth control system for the ROV. This review covered recently published documents for auto-depth control of an Unmanned Underwater Vehicle (UUV). This paper also describes the control issues in UUV especially for the ROV, which has inspired the authors to develop a new technique for auto-depth control of the ROV, called the SIFLC. This technique was the outcome of an investigation and tuning of two parameters, namely the break point and slope for the piecewise linear or slope for the linear approximation. Hardware comparison of the same concepts of ROV design was also discussed. The ROV design is for smallscale, open frame and lower speed. The review on auto-depth control system for ROV, provides insights for readers to design new techniques and algorithms for auto-depth control

IES an open system for underwater inspection

This paper describes the specification and design of a prototype of a low cost open system for the inspection of underwater structures based on a remotely operated underwater vehicle under the project IES, a 3 year long effort funded by the Portuguese R&D program Praxis XXI. Unlike commercial approaches, a modular open system characterised by the incorporation of an on-board computer allowing for advanced control capabilities is envisaged. The control console is based on a standard PC and the tether is used only for power delivery and to establish a simple communication channel. In this project, we use advanced hybrid control techniques for sophisticated semi-autonomous operation management and control. The control architecture reuses part of the one designed for the underwater vehicle Isurus operated by the Laboratory of Underwater Systems and Technologies of Porto University. The implementation is designed in order to allow for multiple sensor configurations specified as add-ins. This leads to a dynamic, scalable and flexible system that can be easily configured according to the user specifications

Towards automated sample collection and return in extreme underwater environments

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Billings, G., Walter, M., Pizarro, O., Johnson-Roberson, M., & Camilli, R. Towards automated sample collection and return in extreme underwater environments. Journal of Field Robotics, 2(1), (2022): 1351–1385, https://doi.org/10.55417/fr.2022045.In this report, we present the system design, operational strategy, and results of coordinated multivehicle field demonstrations of autonomous marine robotic technologies in search-for-life missions within the Pacific shelf margin of Costa Rica and the Santorini-Kolumbo caldera complex, which serve as analogs to environments that may exist in oceans beyond Earth. This report focuses on the automation of remotely operated vehicle (ROV) manipulator operations for targeted biological sample-collection-and-return from the seafloor. In the context of future extraterrestrial exploration missions to ocean worlds, an ROV is an analog to a planetary lander, which must be capable of high-level autonomy. Our field trials involve two underwater vehicles, the SuBastian ROV and the Nereid Under Ice (NUI) hybrid ROV for mixed initiative (i.e., teleoperated or autonomous) missions, both equipped seven-degrees-of-freedom hydraulic manipulators. We describe an adaptable, hardware-independent computer vision architecture that enables high-level automated manipulation. The vision system provides a three-dimensional understanding of the workspace to inform manipulator motion planning in complex unstructured environments. We demonstrate the effectiveness of the vision system and control framework through field trials in increasingly challenging environments, including the automated collection and return of biological samples from within the active undersea volcano Kolumbo. Based on our experiences in the field, we discuss the performance of our system and identify promising directions for future research.This work was funded under a NASA PSTAR grant, number NNX16AL08G, and by the National Science Foundation under grants IIS-1830660 and IIS-1830500. The authors would like to thank the Costa Rican Ministry of Environment and Energy and National System of Conservation Areas for permitting research operations at the Costa Rican shelf margin, and the Schmidt Ocean Institute (including the captain and crew of the R/V Falkor and ROV SuBastian) for their generous support and making the FK181210 expedition safe and highly successful. Additionally, the authors would like to thank the Greek Ministry of Foreign Affairs for permitting the 2019 Kolumbo Expedition to the Kolumbo and Santorini calderas, as well as Prof. Evi Nomikou and Dr. Aggelos Mallios for their expert guidance and tireless contributions to the expedition

State-of-the-Art System Solutions for Unmanned Underwater Vehicles

Unmanned Underwater Vehicles (UUVs) have gained popularity for the last decades, especially for the purpose of not risking human life in dangerous operations. On the other hand, underwater environment introduces numerous challenges in navigation, control and communication of such vehicles. Certainly, this fact makes the development of these vehicles more interesting and engineering-wise more attractive. In this paper, we first revisit the existing technology and methodology for the solution of aforementioned problems, then we try to come up with a system solution of a generic unmanned underwater vehicles

Monitoring of sea-ice-atmosphere interface in the proximity of arctic tidewater glaciers: The contribution of marine robotics

The Svalbard archipelago, with its partially closed waters influenced by both oceanic conditions and large tidal glaciers, represents a prime target for understanding the effects of ongoing climate change on glaciers, oceans, and ecosystems. An understanding of the role played by tidewater glaciers in marine primary production is still affected by a lack of data from close proximity to glacier fronts, to which, for safety reasons, manned surface vessels cannot get too close. In this context, autonomous marine vehicles can play a key role in collecting high quality data in dangerous interface areas. In particular, the contribution given by light, portable, and modular marine robots is discussed in this paper. The state-of-the-art of technology and of operating procedures is established on the basis of the experience gained in campaigns carried out by Italian National Research Council (CNR) robotic researchers in Ny-Alesund, Svalbard Islands, in 2015, 2017, and 2018 respectively. The aim was to demonstrate the capability of an Unmanned Semi-Submersible Vehicle (USSV): (i) To collect water samples in contact with the front of a tidewater glacier; (ii) to work in cooperation with Unmanned Aerial Vehicles (UAV) for sea surface and air column characterisation in the proximity of the fronts of the glaciers; and (iii) to perform, when equipped with suitable tools and instruments, repetitive sampling of water surface as well as profiling the parameters of the water and air column close to the fronts of the tidewater glaciers. The article also reports the issues encountered in navigating in the middle of bergy bits and growlers as well as the problems faced in using some sensors at high latitudes

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

An Overview of AUV Algorithms Research and Testbed at the University of Michigan

This paper provides a general overview of the autonomous underwater vehicle (AUV) research projects being pursued within the Perceptual Robotics Laboratory (PeRL) at the University of Michigan. Founded in 2007, PeRL's research thrust is centered around improving AUV autonomy via algorithmic advancements in sensor-driven perceptual feedback for environmentally-based real-time mapping, navigation, and control. In this paper we discuss our three major research areas of: (1) real-time visual simultaneous localization and mapping (SLAM); (2) cooperative multi-vehicle navigation; and (3) perception-driven control. Pursuant to these research objectives, PeRL has acquired and significantly modified two commercial off-the-shelf (COTS) Ocean-Server Technology, Inc. Iver2 AUV platforms to serve as a real-world engineering testbed for algorithm development and validation. Details of the design modification, and related research enabled by this integration effort, are discussed herein.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86058/1/reustice-15.pd

Underwater Robots Part II: Existing Solutions and Open Issues

National audienceThis paper constitutes the second part of a general overview of underwater robotics. The first part is titled: Underwater Robots Part I: current systems and problem pose. The works referenced as (Name*, year) have been already cited on the first part of the paper, and the details of these references can be found in the section 7 of the paper titled Underwater Robots Part I: current systems and problem pose. The mathematical notation used in this paper is defined in section 4 of the paper Underwater Robots Part I: current systems and problem pose

DeepSurveyCam — A Deep Ocean Optical Mapping System

Underwater photogrammetry and in particular systematic visual surveys of the deep sea are by far less developed than similar techniques on land or in space. The main challenges are the rough conditions with extremely high pressure, the accessibility of target areas (container and ship deployment of robust sensors, then diving for hours to the ocean floor), and the limitations of localization technologies (no GPS). The absence of natural light complicates energy budget considerations for deep diving flash-equipped drones. Refraction effects influence geometric image formation considerations with respect to field of view and focus, while attenuation and scattering degrade the radiometric image quality and limit the effective visibility. As an improvement on the stated issues, we present an AUV-based optical system intended for autonomous visual mapping of large areas of the seafloor (square kilometers) in up to 6000 m water depth. We compare it to existing systems and discuss tradeoffs such as resolution vs. mapped area and show results from a recent deployment with 90,000 mapped square meters of deep ocean floor

Autonomous ROV inspections of aquaculture net pens using DVL

This article presents a method for guiding a remotely operated vehicle (ROV) to autonomously traverse an aquaculture net pen. The method is based on measurements from a Doppler velocity log (DVL) and uses the measured length of the DVL beam vectors to approximate the geometry of a local region of the net pen in front of the ROV. The ROV position and orientation relative to this net pen approximation are used as inputs to a nonlinear guidance law. The guidance law is based upon the line-of-sight (LOS) guidance law. By utilizing that an ROV is fully actuated in the horizontal plane, the crosstrack error is minimized independently of the ROV heading. A Lyapunov analysis of the closed-loop system with this guidance law shows that the ROV is able to follow a continuous path in the presence of a constant irrotational ocean current. Finally, results from simulations and experiments demonstrating the performance of the net pen approximation and control system are presented.acceptedVersio