Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines
Abstract
:1. Introduction
- Reviews the works that have the potential to be implemented within the OWT IMR operations.
- This paper also highlights many strategies that can be implemented as a major enabler toward reaching this goal, including strategies for UVs to perform complex tasks, achieve better localization and navigation, prolong operation time, and establish effective communication.
- Reviews are conducted mostly on related works ranging from 2018 up to 2022.
- Summarizes the main findings related to the potential solutions and improvements a collaborative UVs approach may bring to the unmanned IMR OWT operations.
- Briefly discusses the potential failure modes and redundancies for UVs in the IMR OWT operations and further highlights the importance of exploring redundancies within this area to ensure the reliability, availability, and safety of such collaborative approaches.
2. The State-of-the-Art of UVs Performing in OWT IMR Operations
3. Implementing Collaborative UVs for the OWT IMR Operations
3.1. Strategies to Perform Complex Tasks
3.2. Collaborative Localization and Navigation Strategies
3.3. Collaborative Strategies to Prolong the Operation Time
3.4. Collaborative Communication Strategies
4. Redundancy for Collaborative UVs
4.1. Potential Failure Modes of a Collaborative System
4.2. Redundancy Strategies
5. Conclusions
- Unmanned vehicles such as UAVs, UUVs, or USVs have a very limited capability to perform unmanned IMR operations for OWT when on their own, with the exception of carrying out visual inspections and simple NDT inspections.
- A swarm of drones or homogeneous UVs may accomplish complex IMR tasks but they still depend on USV as a power charging station, to change tools, as a communication hub, etc.
- Many collaborative strategies integrating the UAVs, USVs, UUVs, and crawler robots can be implemented as presented in Table 3, which depends on the degree of task complexity.
- USVs as sources of accurate global positioning (GNSS) may provide reliable and better localization systems for UAVs and UUVs to improve their existing localization system.
- UWB collaborative localization system is currently the best approach for UAVs to work close to an OWT, providing the OWT is shut down temporarily. However, the LiDAR-based SLAM technique has the potential to be implemented while the WT is fully operational.
- The implementation of a USV within a collaborative unmanned network has the potential to solve a number of issues surrounding the unmanned IMR OWT operations, including performing complex tasks, achieving better localization and navigation, prolonging operation time, and establishing better communication.
- Satellite communication system is currently the best communication platform for OWT sectors due to its geolocation. However, the introduction of 5G networks at offshore wind farms is slowly opening up the opportunity for a better communication system.
- At present, there is no redundancy strategy available for the collaborative UV; however, the redundant systems that are currently being deployed for a single UV can be further adapted for the collaborative unmanned systems. Collaborative approaches may also be used to address failure modes in designing redundant systems.
Suggested Future Research Directions
- A collaborative LiDAR-based SLAM localization algorithm can be developed to enable zero-downtime IMR operation for the OWT. This approach can minimize losses of OWT operation due to unwanted shutdown time.
- UVs in terms of a crawler robot or a UAV that can stick firmly to a WTB while in operation without suffering positioning error or odometry failure should be further explored.
- Investigation of a reliable localization and navigation system for UAV utilizing mobile UWB anchors and fixed IMU on an OWT for swaying floating OWT can be further explored.
- Investigation into human-UVs collaboration using tele-operated manipulators for high-skilled OWT maintenance and repair tasks from an inland control station should be carried out.
- Redundancies to address potential failure modes for the collaborative UVs should be further explored and such systems should be devised to ensure the reliability and availability of collaborative UVs for the IMR OWT operations.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
WT | Wind Turbine |
WTB | Wind Turbine Blade |
OWT | Offshore Wind Turbine |
UV | Unmanned Vehicle |
UAV | Unmanned Air Vehicle |
UUV | Unmanned Underwater Vehicle |
USV | Unmanned Surface Vehicle |
ROV | Remotely Operated Vehicle |
BVLOS | Beyond Visual Line of Sight |
GCS | Ground Control Station |
AUV | Autonomous Underwater Vehicle |
NDT | Non-Destructive Testing |
IMR | Inspection, Maintenance, and Repair |
O&M | Operation and Maintenance |
UWB | Ultra-wide Band |
GNSS | Global Navigation Satellite System |
SLAM | Simultaneous Localization and Mapping |
LiDAR | Light Detection and Ranging |
IMU | Inertial Measurement Unit |
RTK | Real-time Kinematics |
PPP | Precise Point Positioning |
PPK | Post-processed Kinematics |
R-LOAM | Reference LiDAR-based Odometry and Mapping |
FMEA | Failure Modes and Effects Analysis |
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Types | Ref. | Purposes | Methods | Application |
---|---|---|---|---|
UAV-USV | [44] | Recovery |
| General |
[45] | Recovery |
| General | |
[46] | Communication platform |
| General | |
[47] | Path planning, navigation, communication platform |
| Monitoring of rivers and dams | |
[48] | Recovery, transportation |
| General | |
[49] | Recovery |
| General | |
[50] | Launch and recovery |
| General | |
[51] | Communication platform |
| General | |
[52] | Power supply |
| Monitoring of water pollution | |
[53] | Power supply |
| General | |
USV-UUV | [54] | Localization |
| General |
[55] | Launch and recovery |
| Surveying of ports and critical infrastructure | |
[56] | Recovery |
| General | |
[57] | Localization, power supply, communication hub |
| Underwater survey | |
UAV-UUV | [58] | Navigation |
| Survey and waste management |
[59] | Communication platform |
| Underwater survey | |
UAV-USV-UUV | [60] | Mission planning, path planning, localization, navigation |
| Surveying of floating targets |
[61] | Path planning |
| Underwater, search-and-track mission | |
[62] | Communication platform |
| General | |
[63] | Power supply, communication platform |
| Inspection and survey missions on offshore infrastructures | |
USV-UAV-CR | [24] | Transportation, power supply |
| IMR for offshore wind farms. |
End Effector | Ref. | Special Features | Potential Collaboration/Adaptation Methods |
---|---|---|---|
Manipulator | [66] | An elastic gripper with a grip and release mechanism. | An automated tools magazine can be placed on a USV platform where a UAV will fly over it and select a desirable tool to exchange by grasping or releasing. |
[67] | A 2-Degree-of-Freedom servomotors-based gripper with 360 degrees of rotation. | With a rotating gripper mechanism, a UAV will have greater flexibility to pick up tools on a USV which is placed without fixed orientation. | |
Single-arm | [43] | For crawler deployment and retrieval. | Using a 6-Degree-of-Freedom robotic arm integrated with a UAV capable of retrieving a crawler robot on a specialized platform onboard a USV. |
[68] | Replaceable robotic arm. | Several robotic arms can be placed on a USV where a UAV will have the flexibility to choose a suitable single robotic arm (different degrees of freedom) for different applications. | |
[69] | Equipped with a gimbal and a dynamic gravity compensation mechanism. | This UAV will have greater control flexibility while acquiring a tool onboard a swaying USV. The mechanism allows the motion of a robotic arm to be decoupled from a drone, ensuring flight stability while the arm is being operated. | |
Multiple arms | [37] | Dual robotic arms for carrying up to 10 kg of payload. | This UAV has the ability to fetch and carry bigger or longer tools which are transported on a USV for the purpose of IMR operations. |
[70] | Equipped with three robotic arms with ultrasonic sensors for landing on uneven surfaces. | This UAV has the ability to carry and transport more objects to IMR sites. It also has the potential to perform preprocessing tasks such as preassembling objects while still onboard a USV. |
Collaborative UVs | Strategies | Benefits | Challenges |
---|---|---|---|
USV-UAV | A USV carrying a fixed-tool UAV |
|
|
A USV carrying a tool-changing UAV |
|
| |
A USV carrying multiple arms UAV |
|
| |
USV-UAVsUSV-UAVs | A large USV carrying multiple fixed-tool UAVs |
|
|
A large USV carrying multiple tool-changing UAVs |
|
| |
A large USV carrying multiple-arm UAVs |
|
| |
A large USV carrying heterogeneous UAVs |
|
| |
USV-UUV | A USV carrying a tool-changing UUV |
|
|
A USV carrying UVMS |
|
| |
USV-UUVs | A large USV carrying multiple tool-changing UUVs |
|
|
A large USV carrying multiple UVMSs |
|
| |
A large USV carrying heterogeneous UUVs |
|
| |
Multiple USVs-UAVs/UUVs | Multiple USVs carrying UAVs or UUVs |
|
|
UAV-Crawler | UAV carrying a robotic crawler |
|
|
Ref. | Localization Methods | Descriptions |
---|---|---|
[83] | Simultaneous model fitting and pose estimation. | Positional accuracy can be achieved through precise image measurements which are based on an optimization algorithm. |
[84] | Robust visual-inertial odometry with point and line features. | A faster line detector and purified strategies enable the detection of wind turbine blades by extracting sufficient features. Fusion of IMU and point-line features exhibit higher accuracy. |
[85] | Visual SLAM with a synthetic depth map. | Using a monocular SLAM system, a visual-based localization system to detect wind turbine blades is improved using a synthetic depth map. The depth map is based on a Line Segment Detector. |
[86] | Autonomous visual navigation algorithm using image processing methods and blade feature detection method. | Using Wavelets, Wiener filtering for a deblurring system, image enhancement using Retinex, and Hough transform for wind turbine edge detection. Blade feature detection is performed by comparing the extracted features (circle and linear features) with the features from a blade library. |
[87] | Visual SLAM. | Focussing on localization within the internal wind turbine blade, localization and navigation can be achieved using the Visual SLAM method. To build a map for localization and navigation, V-SLAM uses distinguished features such as edges, corners, or colours. |
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Share and Cite
Nordin, M.H.; Sharma, S.; Khan, A.; Gianni, M.; Rajendran, S.; Sutton, R. Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines. Drones 2022, 6, 137. https://doi.org/10.3390/drones6060137
Nordin MH, Sharma S, Khan A, Gianni M, Rajendran S, Sutton R. Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines. Drones. 2022; 6(6):137. https://doi.org/10.3390/drones6060137
Chicago/Turabian StyleNordin, Mohd Hisham, Sanjay Sharma, Asiya Khan, Mario Gianni, Sulakshan Rajendran, and Robert Sutton. 2022. "Collaborative Unmanned Vehicles for Inspection, Maintenance, and Repairs of Offshore Wind Turbines" Drones 6, no. 6: 137. https://doi.org/10.3390/drones6060137