TY - GEN
T1 - Path Planning and Control for Remotely Operated Vehicles Focused on Autonomous Visual Inspection of Floating Offshore Wind Structure
AU - Santos, Phillipe
AU - Omerdic, Edin
AU - Santos, Matheus
AU - Fitzgerald, Luke
AU - Fahy, Cillian
AU - Musselwhite-Veitch, H.
AU - Weir, Anthony
AU - Dooly, Gerard
AU - Toal, Daniel
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper introduces an innovative approach to address the challenges of inspecting offshore wind turbines by presenting a real-time dynamic path-planning system for remotely operated vehicles (ROVs). Focused on floating wind turbine structures, the proposed methodology integrates an Inertial Measurement Unit (IMU) into the structure, allowing dynamic adjustment of the inspection path based on real-time pose data. Utilizing a fault-tolerant control solution, the system enables autonomous flight control of ROVs, maintaining consistent orientation towards the structure and desired inspection distance. The applicability of the approach is validated through simulations in the OceanRINGS+ control suite, emphasizing the importance of dynamic path planning in enhancing efficiency, safety, and cost-effectiveness in offshore wind turbine inspections.
AB - This paper introduces an innovative approach to address the challenges of inspecting offshore wind turbines by presenting a real-time dynamic path-planning system for remotely operated vehicles (ROVs). Focused on floating wind turbine structures, the proposed methodology integrates an Inertial Measurement Unit (IMU) into the structure, allowing dynamic adjustment of the inspection path based on real-time pose data. Utilizing a fault-tolerant control solution, the system enables autonomous flight control of ROVs, maintaining consistent orientation towards the structure and desired inspection distance. The applicability of the approach is validated through simulations in the OceanRINGS+ control suite, emphasizing the importance of dynamic path planning in enhancing efficiency, safety, and cost-effectiveness in offshore wind turbine inspections.
KW - inspection
KW - intervention
KW - offshore wind farms
KW - robots
KW - ROV
UR - http://www.scopus.com/inward/record.url?scp=85206455143&partnerID=8YFLogxK
U2 - 10.1109/OCEANS51537.2024.10682326
DO - 10.1109/OCEANS51537.2024.10682326
M3 - Conference contribution
AN - SCOPUS:85206455143
T3 - Oceans Conference Record (IEEE)
BT - OCEANS 2024 - Singapore, OCEANS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - OCEANS 2024 - Singapore, OCEANS 2024
Y2 - 15 April 2024 through 18 April 2024
ER -
