2024
Authors
Claro, R; Neves, F; Pereira, P; Pinto, A;
Publication
Oceans Conference Record (IEEE)
Abstract
With the expansion of offshore infrastructure, the necessity for efficient Operation and Maintenance (O&M) procedures intensifies. This article introduces DADDI, a multimodal dataset obtained from a real offshore floating structure, aimed at facilitating comprehensive inspections and 3D model creation. Leveraging Unmanned Aerial Vehicles (UAVs) equipped with advanced sensors, DADDI provides synchronized data, including visual images, thermal images, point clouds, GNSS, IMU, and odometry data. The dataset, gathered during a campaign at the ATLANTIS Coastal Testbed, offers over 2500 samples of each data type, along with intrinsic and extrinsic sensor calibrations. DADDI serves as a vital resource for the development and evaluation of algorithms, models, and technologies tailored to the inspection, monitoring, and maintenance of complex maritime structures. © 2024 IEEE.
2024
Authors
Leitão, J; Pereira, P; Campilho, R; Pinto, A;
Publication
Oceans Conference Record (IEEE)
Abstract
Accurate dynamics modelling of Unmanned Under-water Vehicles (UUV s) is critical for optimizing mission planning, minimizing collision risks, and ensuring the successful execution of tasks in diverse underwater environments. This paper presents a structured approach to estimating the hydrodynamic coeffi-cients of UUV s. Initially, it follows a detailed methodology for estimating hydrodynamic coefficients using simple geometries, a sphere and a spheroid, using the Computational Fluid Dy-namics (CFD) software OpenFoam, and comparing the results to analytical solutions, enabling the validation of the simulations approach. Following this, the paper provides an in-depth analysis of the damping and added mass coefficients for the Raya UUV, offering valuable insights into its hydrodynamic behaviour. © 2024 IEEE.
2024
Authors
Leite, PN; Pereira, PN; Dionisío, JMM; Pinto, AM;
Publication
OCEAN ENGINEERING
Abstract
Offshore wind farms face harsh maritime conditions, prompting the use of sacrificial anodes to prevent rapid structural degradation. Regular maintenance and replacement of these elements are vital to ensure ongoing corrosion protection, maintain structural integrity, and optimize efficiency. This article details the design and validation of the MARESye hybrid underwater imaging system, capable of retrieving heterogeneous tri-dimensional information with millimetric precision for the close-range inspection of submerged critical structures. The optical prowess of the system is first validated during low turbidity trials where the volumetric properties of a decommissioned anode are reconstructed with absolute errors down to 0.0008 m, and its spatial dimensions are depicted with sub-millimeter precision accounting for relative errors as low as 0.31%. MARESye is later equipped as payload in a commercial ROV during areal environment inspection mission at the ATLANTIS Coastal Test Center. This experiment sees the sensor provide live reconstructions of a sacrificial anode, revealing a biofouling layer of approximately 0.0130 m thickness. The assessment of the high-fidelity 2D/3D information obtained from the MARESye sensor demonstrates its potential to enhance the situational awareness of underwater vehicles, fostering reliable O&M procedures.
2024
Authors
Pinto, AM; Matos, A; Marques, V; Campos, DF; Pereira, MI; Claro, R; Mikola, E; Formiga, J; El Mobachi, M; Stoker, J; Prevosto, J; Govindaraj, S; Ribas, D; Ridao, P; Aceto, L;
Publication
Robotics and Automation Solutions for Inspection and Maintenance in Critical Infrastructures
Abstract
This chapter presents the use of Robotics in the Inspection and Maintenance of Offshore Wind as another highly challenging environment where autonomous robotics systems and digital transformations are proving high value. © 2024 Andry Maykol Pinto | Aníbal Matos | João V. Amorim Marques | Daniel Filipe Campos | Maria Inês Pereira | Rafael Claro | Eeva Mikola | João Formiga | Mohammed El Mobachi | Jaap-Jan Stoker | Jonathan Prevosto | Shashank Govindaraj | David Ribas | Pere Ridao | Luca Aceto.
2024
Authors
Pensado, E; López, F; Jorge, H; Pinto, A;
Publication
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
Abstract
This article presents a real-time trajectory optimizer for shore-to-ship operations using Unmanned Aerial Vehicles (UAVs). This concept aims to improve the efficiency of the transportation system by using UAVs to carry out parcel deliveries to offshore ships. During these operations, UAVs would fly relatively close to manned vessels, posing significant risks to the crew in the event of any incident. Additionally, in these areas, UAVs are exposed to meteorological phenomena such as wind gusts, which may compromise the stability of the flight and lead to potential collisions. Furthermore, this is a phenomenon difficult to predict, which poses a risk that must be considered in the operations. For these reasons, this work proposes a gust-aware multi-objective optimization solution for calculating fast and safe trajectories, considering the risk of flying in areas prone to the formation of intense gusts. Moreover, the system establishes a risk buffer with respect to all vessels to ensure compliance with EASA (European Union Aviation Safety Agency) regulations. For this purpose, Automatic Identification System (AIS) data are used to determine the position and velocity of the different vessels, and trajectory calculations are periodically updated based on their motion. The system computes the minimum-cost trajectory between the ground base and a moving destination ship while keeping these risk buffer constraints. The problem was solved through an Optimal Control formulation discretized on a dynamic graph with time-dependent costs and constraints. The solution was obtained using a Reaching Method that allowed efficient and real-time computations.
2024
Authors
Martins, J; Pereira, P; Campilho, R; Pinto, A;
Publication
2024 20TH IEEE/ASME INTERNATIONAL CONFERENCE ON MECHATRONIC AND EMBEDDED SYSTEMS AND APPLICATIONS, MESA 2024
Abstract
Due to the difficult access to the maritime environment, cooperation between different robotic platforms operating in different domains provides numerous advantages when considering Operations and Maintenance (O&M) missions. The nest Uncrewed Surface Vehicle (USV) is equipped with a parallel platform, serving as a landing pad for Uncrewed Aerial Vehicle (UAV) landings in dynamic sea states. This work proposes a methodology for short term forecasting of wave-behaviour using Fast Fourier Transforms (FFT) and a low-pass Butterworth filter to filter out noise readings from the Inertial Measurement Unit (IMU) and applying an Auto-Regressive (AR) model for the forecast, showing good results within an almost 10-second window. These predictions are then used in a Model Predictive Control (MPC) approach to optimize trajectory planning of the landing pad roll and pitch, in order to increase horizontality, consistently mitigating around 80% of the wave induced motion.
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