Underwater Robotic Vehicles Research Articles

An Integrated System for Geophysical Navigation of Autonomous Underwater Vehicles.

This paper presents a geophysical navigation system for small, affordable underwater robotic vehicles that exploits the information provided by geomagnetic features observed on the seafloor in order to correct the unavoidable drift in position error incurred by dead-reckoning navigation. The approach described combines a sequential estimation algorithm previous developed by the authors with a complementary profile correlation method. The outcome of this integration enhances the estimated position of a marine robotic vehicle in difficult operation conditions.

Lighting System Packaging for Smart Underwater Reefs for Sensing, Communications, and Robotics

Abstract Strings and ropes are a proven, common fisheries and aquaculture construction elements outside the US. Using them as scaffolding also enables a diversity of ocean sensing, communications and architectures, including our goal of sentinel reefs. Packaging of electronics is key to enabling such structures and systems. Our research is towards a demonstrable science-engineering-informed framework for 3D habitat designs critical to stock fish development & coastal protection. These ‘nature-inspired’ reef infrastructures, can enable novel instrumented ‘reef observatories’ capable of collecting real-time ecosystem data. Embedding lighting and electronic elements into reef systems are the first systems in development. This new approach of bringing light to the underwater world for optical sensing, communication and even a new breed of underwater robotic vehicle is an interdisciplinary research activity which integrates principles of electronic packaging, and STEM with art/design.

Viable Alternative Mine Operating System: A novel underwater robotic excavation system for flooded open-cut mines.

The ¡VAMOS! Project (Viable Alternative Mine Operating System) is developing a novel underwater excavation system to test the technological and economic viability of the mining of inland mineral deposits in flooded open-cut mines, currently uneconomic using conventional methods. A floating launch and recovery vessel has been built, and in July 2017, work will be completed on a remotely-operated underwater roadheader and robotic assistance vehicle. After completion, the first of two European trials will commence. During these trials, the road-transportable system will be tested on a range of rock-types and its technological and economic viability and socio-environmental impact will be analysed.

Robust methods of magnetic navigation of marine robotic vehicles

This paper describes the development of robust estimation methods of magnetic navigation for small, affordable underwater robotic vehicles. Relying on prior work by the authors, the paper proposes a particle filter navigation algorithm which is integrated with other position estimation methods to increase the robustness of the estimation process. The new techniques embedded in the navigation particle filter include an adaptive-likelihood particle filter and a magnetic contour matching algorithm implemented in the Fourier domain to achieve superior computation speeds. The performance of the navigation methods proposed is assessed through a series of tests which exploit real data acquired in the water with a marine robotic vehicle. The results obtained illustrate the high potential of the approach for magnetic navigation of autonomous underwater vehicles.

On intelligent risk analysis and critical decision of underwater robotic vehicle

The marine community has witnessed a remarkable growth of underwater robotic vehicles (URVs) for undersea exploration and exploitation in recent decades. Yet, it is critical to intelligently diagnose the fault and evaluate the risk of the onboard system, and render critical decision to ensure the safety of the URV with high-value assets. In this paper, a dedicated two-layer fault treatment system including risk analysis subsystem and intelligent decision subsystem is proposed to enhance the onboard safety of the URV. First, a hierarchical fault tree model of the URV is built by integrating the state information of sensors, actuators and running status. Second, in the risk analysis subsystem, the onboard system risk is analyzed based on the adaptive learning and fuzzy inference capabilities of the Mamdani fuzzy neural network (MFNN). Third, in the safety decision subsystem, the risk level of the URV is evaluated by adopting the maximum membership and threshold principles, which enables the intelligent decision to take critical operation and ensure the safety of the URV. Finally, the proposed fault treatment system is validated by numerical simulation and hardware in loop test. Experimental results demonstrate the feasibility and efficiency of the intelligent fault treatment system for the URV.

Advanced Control in Marine Mechatronic Systems: A Survey

This paper surveys the recent advances in marine mechatronic systems from a control perspective. The survey is by no means exhaustive, but introduces some notable results in marine control area. New developments in terms of control system designs for surface vessels, underwater robotic vehicles, profiling floats, underwater gliders, wave energy converters, and offshore wind turbines are briefly reviewed. In addition, a few avenues for future research are identified.

Trajectory Tracking With Prescribed Performance for Underactuated Underwater Vehicles Under Model Uncertainties and External Disturbances

This paper addresses the tracking control problem of 3-D trajectories for underactuated underwater robotic vehicles. Our recent theoretical results on the prescribed performance control of fully actuated nonlinear systems are innovatively extended on the control of the most common types of underactuated underwater vehicles, namely, the torpedo-like (i.e., vehicles actuated only in surge, pitch, and yaw) and the unicycle-like (i.e., vehicles actuated only in surge, heave, and yaw). The main contributions of this paper concentrate on: 1) the reduced design complexity; 2) the increased robustness against system uncertainties; 3) the prescribed transient and steady-state performance; and 4) the minimal tracking information requirements. A comparative simulation study points out the intriguing performance properties of the proposed method, while its applicability is experimentally verified using a small unicycle-like underactuated underwater vehicle in a test tank.

Reduced Attitude Control of a Robotic Underwater Vehicle

This paper deals with stabilization and reduced attitude control of a robotic underwater vehicle. The vehicle is assumed to be able to perform a full stable rotations around all axes in underwater space, that is why the standard bottom-heavy structure is not used. The system preferably uses a vectored-thrust arrangement and is built as an overactuated system, which enables to gain a better robustness and guarantees a stable controlled motion even if some thruster suddenly stop working. Because the heading angle cannot be measured, the reduced attitude control strategy is designed and the stability of reduced state of the system is proved using perturbation method.

Nonlinear Control of Underwater Robotic Vehicle in Plane Motion

Abstract A control system supporting motion of an underwater robotic vehicle along a reference trajectory in the horizontal plane is presented in the paper. A waypoint line-of-sight scheme and nonlinear PD control law are applied to calculate command signals. Parameters of the proposed control law are tuned using genetic algorithms. The validity and advantages of the approach are illustrated through numerical simulation results.

Design and Experimental Validation of a USBL Underwater Acoustic Positioning System.

This paper presents the steps for developing a low-cost POrtableNavigation Tool for Underwater Scenarios (PONTUS) to be used as a localization device for subsea targets. PONTUS consists of an integrated ultra-short baseline acoustic positioning system aided by an inertial navigation system. Built on a practical design, it can be mounted on an underwater robotic vehicle or be operated by a scuba diver. It also features a graphical user interface that provides information on the tracking of the designated target, in addition to some details on the physical properties inside PONTUS. A full disclosure of the architecture of the tool is first presented, followed by thorough technical descriptions of the hardware components ensemble and the software development process. A series of experiments was carried out to validate the developed prototype, and the results are presented herein, which allow assessing its overall performance.

Robust particle filter formulations with application to terrain‐aided navigation

SummaryThe work described in this paper is motivated by the need to develop efficient and robust estimation filters with application to terrain‐aided navigation of underwater robotic vehicles. One of the main problems addressed is the development of navigation particle filters that can deal with the scarcity of landmarks and the terrain ambiguity that characterize vast regions of the ocean floor. As a contribution to solve this problem, the paper proposes three novel particle filter algorithms and assesses their estimation efficiency and robustness to non‐informative measurements using two well‐known benchmarking tests. The performance of the new filters in these tests demonstrates their potential to solve a class of nonlinear problems that include, but are not limited to, the type of underwater navigation problem that motivated the present work. Our study concludes by examining the performance of the filters in terms of determining the position and velocity of an autonomous underwater vehicle in the presence of unknown ocean currents. When applied to terrain‐aided navigation, the novel particle filter formulations formulations mitigate filter divergence issues frequently caused by terrain symmetries and are more robust than other well‐known versions when used in scenarios with poor terrain information. The theoretical developments presented and the results obtained in simulations are validated using real data acquired during tests with an autonomous marine robot. Copyright © 2016 John Wiley & Sons, Ltd.

Experimental validation of magnetic navigation of marine robotic vehicles

Abstract: This paper describes the work developed towards the implementation of magnetic navigation (MAGNAV) methods for small, affordable underwater robotic vehicles. MAGNAV constitutes a particular implementation of a broader class of methods designated as geophysical navigation, which encompasses the already classical terrain-aided, or terrain-referenced, navigation approach. Relying on prior work by the authors, the paper proposes a particle filter navigation algorithm which may be combined with other position estimation methods to increase the robustness of the estimation process. The results of a series of tests performed in the water with a marine robotic vehicle in order to assess the impact of different sensor-vehicle configurations on the quality of the magnetic data used in MAGNAV are reported. The magnetic navigation solution proposed is validated in simulated trials using real magnetic and navigation data acquired with an autonomous marine vehicle in real trials using standard navigation sensors and an affordable total field magnetometer. The results obtained illustrate the high potential of the approach for geophysical navigation of autonomous underwater vehicles.

Modelling of Underwater Robotic Vehicle Motion with Using of Genetic Algorithms

The utilization of underwater robotic vehicles has known an increasing importance in many marine activities. The robotic vehicle is equipped with a propulsion system and controlled by a human operator. To simplify tasks of the operator, a control system guaranteeing the automation of elementary robot’s behaviours is often applied. In the paper, a control system supporting the robot spatial motion along a reference path is presented. A waypoint line-of-sight scheme is incorporated and Genetic Algorithms are applied to calculate command signals. Selected results of computer simulations are inserted to demonstrate quality and correctness of the proposed approach.

Bio-harmonized control experiments of a carangiform robotic fish underwater vehicle

This paper presents experimental implementation and comparison of three different control schemes of a bio-inspired robotic fish underwater vehicle. The dynamics model is obtained by unifying conventional rigid body dynamics and bio-fluid dynamics of a carangiform fish swimming given by Lighthill’s(LH) slender body theory. It proposes an inclusive mathematical design for better control and energy efficient path travel for the robotic fish. The system is modeled as an two-link robot manipulator (caudal tail) with a mobile base (head). This forward thrust drives the robotic fish head represented by a combined non-linear equation of motion in earth fixed frame. We develop and compare the dynamic motion closed loop control strategy of the bio-harmonized robotic fish based on three different non-linear control schemes using CTM (Computed Torque Method), FF (Feed-Forward) controllers both with dynamic PD compensation and finally a proposed combination of CTM with FF. An inverse dynamic control method based on non-linear state function model including hydrodynamics is proposed to improve tracking performance. CTM control generates a feedback loop for linearization and decoupling robot dynamic model with a shorter response time, while a dynamic PD compensation in the FF path is employed by FF scheme through the desired trajectories. FF model-based strategy results in an improved tracking and shorter route to travel between two points. Overall results indicate that performances of the proposed control schemes based on the inverse dynamic model are comparable and useful for robotic fish motion tracking in fluid environment.

Python and MatPlotLib based Open Source Software System for Simulating Images with point Light Sources in Attenuating and Scattering Media

Simulating images of various objects in a real world scene has wide applications while testing algorithms for machine vision applications as well as in computer graphics and gaming software industry. Most current algorithms use collimated light sources and assume the medium to be non-scattering and non-attenuating. In real world, most light sources are too near to the objects in the scene and hence cannot be assumed to be collimated. Real world mediums, such as oceans in case of Underwater Robotic Vehicle (URV) applications or smoke and vapor filled air in case of industrial welding applications, scatter and attenuate light. A software system that makes no such assumptions and uses point light sources in scattering and attenuating media has been developed. Another novelty of current work is use of open source Python programming language along with associated 2D graphics and plotting library, MatPlotLib. General Terms Underwater Robotic Vehicles, Industrial Robots, Image simulation, Python, MatPlotLib.

Influence of ice thickness and surface properties on light transmission through Arctic sea ice.

The observed changes in physical properties of sea ice such as decreased thickness and increased melt pond cover severely impact the energy budget of Arctic sea ice. Increased light transmission leads to increased deposition of solar energy in the upper ocean and thus plays a crucial role for amount and timing of sea‐ice‐melt and under‐ice primary production. Recent developments in underwater technology provide new opportunities to study light transmission below the largely inaccessible underside of sea ice. We measured spectral under‐ice radiance and irradiance using the new Nereid Under‐Ice (NUI) underwater robotic vehicle, during a cruise of the R/V Polarstern to 83°N 6°W in the Arctic Ocean in July 2014. NUI is a next generation hybrid remotely operated vehicle (H‐ROV) designed for both remotely piloted and autonomous surveys underneath land‐fast and moving sea ice. Here we present results from one of the first comprehensive scientific dives of NUI employing its interdisciplinary sensor suite. We combine under‐ice optical measurements with three dimensional under‐ice topography (multibeam sonar) and aerial images of the surface conditions. We investigate the influence of spatially varying ice‐thickness and surface properties on the spatial variability of light transmittance during summer. Our results show that surface properties such as melt ponds dominate the spatial distribution of the under‐ice light field on small scales (<1000 m2), while sea ice‐thickness is the most important predictor for light transmission on larger scales. In addition, we propose the use of an algorithm to obtain histograms of light transmission from distributions of sea ice thickness and surface albedo.

Control Libre de Modelo basado en Modos Deslizantes Integrales para Robots Submarinos Subactuados

A combination of a model-free control law at the dynamic level and a guidance law at the kinematic level is proposed for the tracking of an underactuated underwater robot vehicle. The closed-loop system gives rise to chattering-free integral sliding modes for local exponential tracking of actuated coordinates, while ensuring a global stable internal dynamics under certain conditions easy to meet in practice. The design methodology relies on a careful manipulation of the quasi-lagrangian model of the underwater vehicle with a control law that is independent of dynamic model and its parameters assuming full access to the state. Comparative simulations versus a PID show the feasibility and robust behavior under parametric and model uncertainties.

MEMS sensors for assessing flow-related control of an underwater biomimetic robotic stingray

A major difference between manmade underwater robotic vehicles (URVs) and undersea animals is the dense arrays of sensors on the body of the latter which enable them to execute extreme control of their limbs and demonstrate super-maneuverability. There is a high demand for miniaturized, low-powered, lightweight and robust sensors that can perform sensing on URVs to improve their control and maneuverability. In this paper, we present the design, fabrication and experimental testing of two types of microelectromechanical systems (MEMS) sensors that benefit the situational awareness and control of a robotic stingray. The first one is a piezoresistive liquid crystal polymer haircell flow sensor which is employed to determine the velocity of propagation of the stingray. The second one is Pb(Zr0.52Ti0.48)O3 piezoelectric micro-diaphragm pressure sensor which measures various flapping parameters of the stingray’s fins that are key parameters to control the robot locomotion. The polymer flow sensors determine that by increasing the flapping frequency of the fins from 0.5 to 3 Hz the average velocity of the stingray increases from 0.05 to 0.4 BL s−1, respectively. The role of these sensors in detecting errors in control and functioning of the actuators in performing tasks like flapping at a desired amplitude and frequency, swimming at a desired velocity and direction are quantified. The proposed sensors are also used to provide inputs for a model predictive control which allows the robot to track a desired trajectory. Although a robotic stingray is used as a platform to emphasize the role of the MEMS sensors, the applications can be extended to most URVs.

Hybrid underwater robotic vehicles: the state-of-the-art and future trends

Most of the ocean resources, which cover over 70% of the Earth's surface, are not well discovered or explored. For decades, ocean communities have resorted to underwater robotic vehicles (URVs), remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs) to replace human beings or manned underwater vehicles (MUVs) on deep underwater activities. Combining the advantages of ROVs and AUVs, a new type of underwater explorer named the hybrid underwater robotic vehicle (HURV) has been developed for both deep-sea exploration and intervention by switching its dual-operation modes for accomplishing underwater tasks during one single cruise deployment. This paper presents an overview of the state-of-the-art URV system, where the HURV system is the main concern. The concept of the HURV is introduced via a comparison with other underwater vehicles, after which the thinking behind the HURV design is examined and the operational procedure of the HURV is described. Subsequently, the specifications and ca...

A Novel Iterative Algorithm for Recovering Shape and 3D Information using Photometric Stereo with Point Light Sources in Attenuating and Scattering Media

When photometric stereo technique is used to recover shape and 3D information of an object from multiple images, it is common to assume that the light sources being used are collimated. When the light sources that are being used are actually point light sources, as in robot applications for weld seam inspection or underwater imaging, such an assumption causes significant error. The error increases further when the imaging system is deployed in an attenuating and scattering media. In such situations, a purely analytical solution is not possible. Current work proposes a novel iterative algorithm for recovering shape and 3D information in such situations. General Terms Underwater Robotic Vehicles, Industrial Robots, Computer Vision, Algorithm.