Design & Development of Assistive Tools for Future Applications in the Field of Renewable Ocean Energy Edin Omerdic*, Daniel Toal*, Sean Nolan*, Hammad Ahmad* and Garret Duffy** *
University of Limerick, ECE Department, Limerick, Ireland ** NUIGalway, Earth and Ocean Sciences, Galway, Ireland e-mail: {edin.omerdic} {daniel.toal}{sean.nolan}{hammad.ahmad}@ul.ie,
[email protected] Abstract- This paper describes innovations within a set of assistive tools and technologies for system integration, deployment, monitoring, and maintenance of ocean energy devices (wave energy converters and tidal turbines). These tools comprise of simulation, modelling, control and visualisation tools, including modelling of ocean waves, currents, surface and submerged energy converters, marine platforms and supporting vessels (ships and ROVs). The flexible design of these tools enables their use as separate standalone modules, as well as their integration into a unique integrated system. Four main innovations of the proposed system are 2D Advanced Topview Display, Advanced Pilot Interface, 3D Real-Time Augmented Reality Display and Advanced Control System with FaultTolerant Capabilities. System validation and technology demonstration was performed through a series of test trials with different ROVs and support vessels off the west coast of Ireland, in Galway Bay and Shannon Estuary. Selected results of these trials are presented in this paper.
I.
INTRODUCTION
Deployment, installation & maintenance of ocean energy devices require use of underwater robots and support vessels, which are also used by other offshore industry, e.g. oil & gas. These vessels may be very expensive and, moreover, their costs are very volatile, depending on offshore peak demands. Thus, it is important to address the requirements for vessels to be used in ocean energy deployments and how these requirements may be configured to reduce the costs of these vessels and, simultaneously, affect technology development. ROVs have become the workhorse of subsea operations in many sectors. The assistive visualisation and control tools, proposed in this paper, provide operators with better situation awareness and enhanced vehicle control in the presence of disturbances (waves and currents), allowing them to concentrate on the task and to complete the work in a satisfactory manner and in a shorter time. The maritime sector offers a broad variety of applications for advanced computer graphics technology. Review of these applications, based on virtual/augmented reality, is given in [1]. Use of virtual reality in underwater tele-operation and training has been proposed in [2]. Recent advances in highlevel simulators of underwater vehicles are described in [3]. The aim of “Ocean Systems Modelling” project, funded under the Charles Parson’s Energy Research Awards at University of Limerick, is focused on the design and development of a set of assistive tools and technologies for
system integration, deployment, monitoring, and maintenance of ocean energy devices (in particular - wave energy converters and tidal turbines). Research outputs of the project are, however, equally applicable to the larger and growing international off-shore oil and gas sector and the move in this sector to operations in challenging deep water exploration and production. The assistive tools comprise of simulation, modelling, control and visualisation tools, including modelling of ocean waves, currents, surface and submerged energy converters, marine platforms and supporting vessels (ships and ROVs) [4]. The flexible design of these tools enables their use as separate standalone modules, as well as their integration into a unique integrated system. A major component of the system, designed as a prototype platform to demonstrate system validity & operability and to prove new technologies developed in the Mobile and Marine Robotics Research Centre, is a smart remotely operated vehicle ROVLATIS [5]. Operation & maintenance represents a significant share of offshore energy cost. Thus, the development of tools to assist in the design and operation of ocean energy farms has been identified as a research priority [6]. As highlighted in [7], the major obstacles restricting the development of wave and tidal energy devices include high deployment and maintenance costs, due to harsh nature of locations where ocean energy devices are deployed. The assistive tools, developed in the project, will directly address this issue by reducing these costs in two ways: making offshore operations (including ROV operations) easier & more efficient, and saving in expensive support vessel time during deployment, ongoing servicing, maintenance and repair on ocean energy installations. Selected results from the latest test trials in Galway Bay & Shannon Estuary are presented in this paper. These trials were focused on renewable ocean energy observations and measurements (waves, current, seabed form & water column). II. CONCEPT The Assistive Tools comprise of System Core, Real-World Environment and Virtual Environment (Fig. 1). The System Core is built from a set of tools (Simulation Tools, Modelling Tools, Control Tools and Visualisation Tools), which provide an easy and transparent interface between Real-World Environment and Virtual Environment.
Figure 1. The main components of Assistive Tools: System Core, Real-World Environment and Virtual Environment.
Figure 4. System interconnection in Real-World Environment. Figure 2. Real-World Environment: Real Ship (RV Celtic Voyager) & Real ROV (ROVLATIS) are interfaced to System Core.
Simulation PC
Figure 3. Virtual Environment: Virtual Ship (RV Celtic Voyager) & Virtual ROV (ROVLATIS) are interfaced to System Core via Simulation PC.
The views inside the Control Cabin of ROVLATIS during the field trials (Real-World Environment) and lab tests (Virtual Environment) are shown in Fig. 2 & 3, respectively. The RealWorld Environment consists of the following real-world components: • Real ocean energy devices: wave energy point absorbers, tidal stream devices, etc.
Figure 5. System interconnection in Virtual Environment.
• Real ROVs: remotely operated vehicles, used for survey, deployment and maintenance of ocean energy devices. • Real support vessels: ships, boats etc. used as support platforms for launching/recovery of ROVs. In the Real-World Environment each real-world component is subject to real-world disturbances (real waves and real ocean currents) (see Fig. 1). Each real-world component has equivalent virtual component in the Virtual Environment. A virtual component is a mixed hardware/software real-time dynamic system, which is fully input-output compatible with corresponding real-world component on a signal level. This means, for example, that the output message with navigation data for the virtual ROV is sent through the serial ports in the same format as the output of the real inertial navigation system (INS) installed on the ROV (identical message formats including checksums; identical RS232 port settings including baud rate, parity, number of stop bits, etc.). In this way the real-time controllers do not know the origin of data source, i.e. if data is coming from the real-world or virtual instruments. Fig. 4 & 5 show system interconnection in Real-World Environment and Virtual Environment, respectively. This transparency of data sources, together with hardwarein-the-loop (HIL) control devices setup, provides a unique framework to design, develop and test the control system before the actual physical system components, such as ROV or ocean energy device, are built. The ultimate objective (saving ship time & making ROV operations easier) is achieved through: • Improved User Interface (Advanced 2D & 3D displays – better situation awareness), • Advanced Control Modes (Enabling ROV pilots with average skills to achieve exceptional results), • High-Accuracy Nav Data (Easier post-processing & better quality of bathymetry data), • Improved Control Cabin – Bridge Communication (Better synchronisation of ROV & Ship motions),
Figure 6. 2D Topview Display.
Figure 7. 2D Topview Display.
III. INNOVATIONS Four main innovations of the proposed system include 2D Topview Display, Advanced Pilot Interface, 3D Real-Time Augmented Reality Display and Advanced Control System with Fault-Tolerant Capabilities. The 2D Topview Display (Fig. 6) shows topview of the working zone and includes features like auto zoom, nav info display, floating heading indicators, visualisation of way points, real-time visualisation of sensors measurements (INS, DVL, USBL, GPS, etc.), distance & angle measurements tools, etc. The Advanced Pilot Interface (Fig. 7) presents all important control data to ROV pilot using familiar graphic controls & indicators. The pilot is able to use joystick, gamepad, mouse or keyboard as input devices to generate commands and enable/disable low-level controllers.
Figure 8. 3D Real-Time Augmented Reality Display.
Set points can be entered numerically (using numeric control field) or graphically (moving instrument pointer by mouse). The pilot can also easily switch between manual mode, semi-automatic modes (Follow Desired Speed & Course, Keep Current Position and Go To Position) and fully automatic mode (automatic navigation through way points). The 3D Real-Time Augmented Reality Display (Fig. 8) provides 3D real-time visualisation of the support vessel, ROV, ocean energy device, ocean surface, seabed, etc. Virtual components (ocean energy device, ship, ROV) have the same appearance as corresponding real components (same dimension, colour, etc.). They are driven by real-time measurements obtained through component interfaces. Waves on the surface are generated from estimated sea state, while the seabed is built from previous bathymetry data. The control system (Fig. 9) include fast auto-tuning of lowlevel controllers, automatic thruster fault detection and accommodation, semi-automatic and fully-automatic control modes, optimal control allocation of thrusters, etc. More information about control system can be found in [8].
ROV (Fig. 11). A remote display was also set up on the ship bridge, providing enhanced 3D visualisation of the deployed ROV in the water (Fig. 12). The trials verified that assistive tools could be deployed on a vessel of opportunity.
Figure 10. Survey area of cruise CE-10-010.
Figure 9. Advanced Control System with Fault-Tolerant Capabilities.
IV. SYSTEM VALIDATION The performance of the overall system has been successfully validated through a series of test trials off the coast of Connemara, Galway Bay and Shannon Estuary. A. CE-10-010 Cruise In April 2010 visualisation tools were integrated with Irish Marine Institute’s ROV Holland I onboard RV Celtic Explorer during the cruise off the coast of Connemara (see Fig. 10). The core state-of-the-art navigation systems (ixSea PHINS INS, RDI DVL Workhorse, multibeam echosounder Reson 7125, Tritech side-scan sonar, Sound velocity probe, etc.) were integrated with a commercially built SMD ROV Holland I and shipboard systems. In these trials, the 3D Real-Time Augmented Reality Display was installed in the ROV Control Cabin for aiding and improving ROV pilot situation awareness of the deployed
Figure 11. 3D Real-Time Augmented Reality Display inside ROV Control Cabin (water surface removed to improve visibility).
Figure 12. Remote display of 3D Real-Time Augmented Reality Display, integrated on the bridge of RV Celtic Explorer during cruise CE-10-010.
B. CV-10-029 Cruise Full system test and validation of assistive tools was performed during this cruise in August 2010. ROVLATIS was mobilized using the ship RV Celtic Voyager (Fig. 13). The objectives of this research survey were focused on collection of field data for roll out of renewable ocean energy projects (tidal and wave energy) in west coast Ireland using the smart ROVLATIS and ocean sensors. Specifically, this involved the deployment of ROVLATIS equipped with payload instrumentation and use of ship mounted sensor to acquire data in detailed energy farm site analysis and in operations / performance testing of ROVs in support of off shore energy installations. The standard suite of navigation equipment was extended with submersible GPS and leased BlueView forward looking sonar. Selected survey results are reported here. Figure 14. ‘ROV in tow’ work, where ROV is towed along a transect behind the ship (Real-Time Pilot Camera View).
Figure 13. Smart ROVLATIS on the deck of RV Celtic Voyager.
Remote Current/Wave Radar has been acquired by NUIGalway and is being installed at present. The original plans at the time of ship-time application were for the simultaneous acquisition of current and wave data in the field with ROV-mounted instruments to calibrate Remote Current/Wave Radar measurements. Delays in the delivery and commissioning of the wave radar meant it was not operational at the time of the CV-10-029 survey. Regardless of these delays, the MMRRC team performed series of ocean currents measurements in Galway Bay, both on surface and in the water column. Adaptive Doppler Current Profiler (ADCP) data was acquired with both ship mounted ADCP and ROV mounted ADCP instruments in transects across the wave radar scan sector. The ADCP work in Galway Bay (Fig. 14) included a mix of ‘on station’ work with the ship at anchor and ‘ROV in tow’ work with the platform towed along a transect behind the ship. The envelope of ROV manoeuvring performances and operation limits in strong currents was investigated through the dynamic changes in ship’s speed, ROV depth, heading and attitude. 3D Real-Time View of ROV towed behind the ship is shown in Fig. 15 (“bubbles” represent trajectory behind ROV).
Figure 15. Submerged “ROV in tow” performing multi-beam survey and collecting ADCP data simultaneously (3D Real-Time View).
Turn Transect 2 (Speed Mode: Follow Desired Speed & Course)
Change of Speed Mode Transect 1 (Speed Mode: manual control using joystick)
Figure 16. ROV trajectory during multibeam survey of Foynes Port.
the semi-automatic Speed Mode: Follow Desired Speed & Course (Fig. 17), a much smoother trajectory and better turn control was obtained (Fig. 16, Trajectory 2 & Turn). Desired Speed was set to 0.3 m/s, while Desired Course was set with a pointer or numerical control with resolution of 1°. As result of switching to semi-automatic mode, the overall survey was performed in a shorter time, and the quality of raw multibeam data collected during the survey was very high. The final bathymetry of Foynes Port, obtained after post-processing of raw multibeam data, is shown in Fig. 18. Field trials have demonstrated that the application of assistive tools makes offshore operations easier & more efficient, resulting in an estimated cost saving of up to 20%. ACKNOWLEDGMENT
Figure 17. ROV Pilot Interface for Speed Mode: Follow Desired Speed & Course, used during multibeam survey of Foynes Port.
The development of ROVLATIS and of the modelling and operations support tools described has been supported by funding under the Irish Marine Institute and the Marine RTDI Measure, Productive Sector Operational Programme, National Development Plan 2000 – 2006 (PhD -05-004, INF-06-013 and IND-05-03); Science Foundation Ireland under Grant Number 06/CP/E007 (Charles Parsons Energy Research Awards 2006); HEA PRTLI 3 (MSR3.2 project -Deep Ocean Habitat Mapping using and ROV; HEA PRTLI 4 Environment & Climate Change Impacts and Responses Project/ Environment Graduate Programme; and Enterprise Ireland Commercialisation Fund Technology Development 2007 projects – MPPT Ring (CFTD/07/IT/313, "Multi-Purpose Platform Technologies for Subsea Operations) and PULSE RT (CFTD/07/323, "Precision Underwater Accelerated Sonar Emulation in Real Time). REFERENCES [1]
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[6] Figure 18. Foynes Port bathymetry.
The multibeam survey of Foynes Port was performed with ROVLATIS deployed from a stationary ship in surface operation mode. Weather conditions were calm, with strong East-West tidal currents. In order to demonstrate the quality of semiautomatic control modes, ROV was initially controlled manually by joystick (Fig. 16, Transect 1). After switching to
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