Artificial Intelligence in Marine Science and Engineering

This Special Issue covers research in Artificial Intelligence in Marine Science and Engineering and shows how to apply it to many different professional areas, e [...

Marine Vessel Inspection as a Novel Field for Service Robotics: A Contribution to Systems, Control Methods and Semantic Perception Algorithms.

This cumulative thesis introduces a novel field for service robotics: the inspection of marine vessels using mobile inspection robots. In this thesis, three scientific contributions are provided and experimentally verified in the field of marine inspection, but are not limited to this type of application. The inspection scenario is merely a golden thread to combine the cumulative scientific results presented in this thesis. The first contribution is an adaptive, proprioceptive control approach for hybrid leg-wheel robots, such as the robot ASGUARD described in this thesis. The robot is able to deal with rough terrain and stairs, due to the control concept introduced in this thesis. The proposed system is a suitable platform to move inside the cargo holds of bulk carriers and to deliver visual data from inside the hold. Additionally, the proposed system also has stair climbing abilities, allowing the system to move between different decks. The robot adapts its gait pattern dynamically based on proprioceptive data received from the joint motors and based on the pitch and tilt angle of the robot's body during locomotion. The second major contribution of the thesis is an independent ship inspection system, consisting of a magnetic wall climbing robot for bulkhead inspection, a particle filter based localization method, and a spatial content management system (SCMS) for spatial inspection data representation and organization. The system described in this work was evaluated in several laboratory experiments and field trials on two different marine vessels in close collaboration with ship surveyors. The third scientific contribution of the thesis is a novel approach to structural classification using semantic perception approaches. By these methods, a structured environment can be semantically annotated, based on the spatial relationships between spatial entities and spatial features. This method was verified in the domain of indoor perception (logistics and household environment), for soil sample classification, and for the classification of the structural parts of a marine vessel. The proposed method allows the description of the structural parts of a cargo hold in order to localize the inspection robot or any detected damage. The algorithms proposed in this thesis are based on unorganized 3D point clouds, generated by a LIDAR within a ship's cargo hold. Two different semantic perception methods are proposed in this thesis. One approach is based on probabilistic constraint networks; the second approach is based on Fuzzy Description Logic and spatial reasoning using a spatial ontology about the environment

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Dynamic Guarding of Marine Assets Through Cluster Control of Automated Surface Vessel Fleets

There is often a need to mark or patrol marine areas in order to prevent boat traffic from approaching critical regions, such as the location of a high-value vessel, a dive site, or a fragile marine ecosystem. In this paper, we describe the use of a fleet of robotic kayaks that provides such a function: the fleet circumnavigates the critical area until a threatening boat approaches, at which point the fleet establishes a barrier between the ship and the protected area. Coordinated formation control of the fleet is implemented through the use of the cluster-space control architecture, which is a full-order controller that treats the fleet as a virtual, articulating, kinematic mechanism. An application-specific layer interacts with the cluster-space controller in order for an operator to directly specify and monitor guarding-related parameters, such as the spacing between boats. This system has been experimentally verified in the field with a fleet of robotic kayaks. In this paper, we describe the control architecture used to establish the guarding behavior, review the design of the robotic kayaks, and present experimental data regarding the functionality and performance of the system.Fil: Mahacek, Paul. Santa Clara University; Estados UnidosFil: Kitts, Christopher A.. Santa Clara University; Estados UnidosFil: Mas, Ignacio Agustin. Santa Clara University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

AN INTELLIGENT NAVIGATION SYSTEM FOR AN AUTONOMOUS UNDERWATER VEHICLE

The work in this thesis concerns with the development of a novel multisensor data fusion (MSDF) technique, which combines synergistically Kalman filtering, fuzzy logic and genetic algorithm approaches, aimed to enhance the accuracy of an autonomous underwater vehicle (AUV) navigation system, formed by an integration of global positioning system and inertial navigation system (GPS/INS). The Kalman filter has been a popular method for integrating the data produced by the GPS and INS to provide optimal estimates of AUVs position and attitude. In this thesis, a sequential use of a linear Kalman filter and extended Kalman filter is proposed. The former is used to fuse the data from a variety of INS sensors whose output is used as an input to the later where integration with GPS data takes place. The use of an adaptation scheme based on fuzzy logic approaches to cope with the divergence problem caused by the insufficiently known a priori filter statistics is also explored. The choice of fuzzy membership functions for the adaptation scheme is first carried out using a heuristic approach. Single objective and multiobjective genetic algorithm techniques are then used to optimize the parameters of the membership functions with respect to a certain performance criteria in order to improve the overall accuracy of the integrated navigation system. Results are presented that show that the proposed algorithms can provide a significant improvement in the overall navigation performance of an autonomous underwater vehicle navigation. The proposed technique is known to be the first method used in relation to AUV navigation technology and is thus considered as a major contribution thereof.J&S Marine Ltd., Qinetiq, Subsea 7 and South West Water PL

Cluster Control of Automated Surface Vessels

This research focuses on the design and control of a fleet of robotic kayaks, and presents experimental data regarding the functionality and performance of the system. One of the key technical challenges in fielding multi-robot systems for real-world applications is the coordination and relative motion control of the individual units. Coordinated formation control of the fleet is implemented through the use of the cluster space control architecture, which is a full-order controller that treats the fleet as a virtual, articulating, kinematic mechanism. The resulting system is capable of autonomous navigation utilizing a centralized controller, currently implemented via a shore-based computer that wirelessly receives ASV data and relays control commands. Using the cluster space control approach, these control commands allow a cluster supervisor to oversee a flexible and mobile formation formed by the ASV cluster. This paper includes an extended appendix which includes MatLab and Simulink code as well as two publications completed in the process of this research

Haptic identification by ELM-controlled uncertain manipulator

This paper presents an extreme learning machine (ELM) based control scheme for uncertain robot manipulators to perform haptic identification. ELM is used to compensate for the unknown nonlinearity in the manipulator dynamics. The ELM enhanced controller ensures that the closed-loop controlled manipulator follows a specified reference model, in which the reference point as well as the feedforward force is adjusted after each trial for haptic identification of geometry and stiffness of an unknown object. A neural learning law is designed to ensure finite-time convergence of the neural weight learning, such that exact matching with the reference model can be achieved after the initial iteration. The usefulness of the proposed method is tested and demonstrated by extensive simulation studies. Index Terms—Extreme learning machine; haptic identification; adaptive control; robot manipulator

Continuous Autonomous UAV Inspection for FPSO vessels

This Master's thesis represents the preliminary design study and proposes the unmanned aerial vehicle (UAV) -based inspection framework, comprising several multirotors with automatic charging and deployment for 24/7 integrity inspection tasks. This project has three main topics. First one describes the operational environment and existing regulations that cover use of UAVs. It forms the basis for proposal of the relevant use-case scenarios. Third part comprises two chapters, where design of concept and framework is being based on the previous factors. It shows that before implementation of fully autonomous inspection system, there is a need to cover both regulatory and technical gaps. It can be explained by the fact that there does not exist any autonomous inspection system today. Thus, this project can be seen as a base for future development of the UAV-based inspection system, as it focuses on creation of a general framework