The philosophy behind the HyBIS instrument is to develop a technological solution that addresses the specific requirements of the user. Rather than provide a comprehensive engineering capability in a single system (e.g. an ROV), we used the specific scientific needs of the user to inform the design and development of the technology. The result is surprising: a versatile technology, modular in design, that has a low capital cost and is relatively easy to operate. We believe that this approach is both efficient and cost effective. For a fraction of the capital and running cost of a conventional ROV, the HyBIS system meets many of the users' needs. Ensuring that excess capacity and common formats are designed in from the start, the instrument can be easily expanded and developed to meet future requirements. Key to the success of this approach is knowing exactly what the user needs and distinguishing this from what the user thinks they want. This requires a bi-lateral process of information flow: educating both the engineer and the user so that each knows what can be achieved and what is actually required.

Underwater vehicles operate in dynamic environments where sudden changes of the working conditions occur from time to time. The need of an effective control action calls for refined techniques with a high degree of robustness with respect to large parametric variations and/or uncertainties. Supervised switching control seems to be theoretical frameworks where appropriate control strategies can be developed. In this chapter, a switching adaptive tracking control based on NNs is proposed and compared with an NN-based switching controller. The form of used nets is the RBFN, which has been used successfully in other control system applications (Antonini et al., 2006) and has favourable characteristics in terms of the best approximation property (Poggio & Girosi, 1990). On the basis of numerical tests, the NNSAC is able to cope with the large transient errors related to the considered mode-switch processes, when knowledge of the different possible vehicle configurations is poor. In fact, if the operative conditions are unknown, an NNSC cannot guarantee good control performance; the pre-computed controllers cannot cope with all environment and load conditions. Therefore, the integration of a switching control strategy with adaptive controllers is particularly well suited to cope with these unknown operative conditions and improve the performance of the overall control system when the different environments where the vehicle operates are not well known.

This chapter presents a novel control strategy for trajectory tracking of underwater marine vehicles that are designed using port-Hamiltonian theory. A model for neutrally buoyant underwater vehicles is formulated as a PHS, and then the tracking controller is designed for the horizontal plane-surge, sway and yaw. The control design is done by formulating the error dynamics as a set-point regulation port-Hamiltonian control problem. The control design is formulated in two steps. In the first step, a static-feedback tracking controller is designed, and the second step integral action is added. The global asymptotic stability of the closed loop system is proved and the performance of the controller is illustrated using a model of an open-frame offshore underwater vehicle.

In this chapter Teleo-Reactive Executive (T-REX) is designed, developed, tested and deployed as an onboard adaptive control system that integrates artificial intelligence (AI)-based planning and probabilistic state estimation in a hybrid executive. Probabilistic state estimation integrates a number of science observations to produce a likelihood that the vehicle sensors perceive a feature of interest. Onboard planning and execution enable adaptation of navigation and instrument control based on the probability of having detected such a phenomenon. It further enables goal-directed commanding within the context of projected mission state and allows for replanning for off-nominal situations and opportunistic science events.

This chapter highlights in detail the development of a USV named Springer. The hardware and software architecture of Springer including its sensors suite are discussed in detail. Initial experiments to collect data for modelling purpose are outlined. Details regarding the design of its advanced navigation, guidance and control systems are also presented.

An auxiliary propulsion module for a 200-m Slocum glider has been presented.The module greatly enhances the operational abilities of underwater gliders by enabling horizontal flight and increased speed capabilities. A simplified hydrodynamic model under the assumption of a zero angle of attack was used to design the module. Using this model, the initial component selection was accomplished through matching the motor, gearbox and measured propeller efficiencies. The propulsion module's performance was confirmed through propulsion tests in the flume tank at MUN.

This chapter presents an overview of the work on the RoboSalmon prototype biomimetic underwater vehicle carried out at the University of Glasgow. This work includes the development of the mathematical model that covers the kinematics and dynamics of the RoboSalmon vehicle to assist with the understanding of the dynamics of the swimming process. Details of the method used to model the tendon drive propulsion system are presented along with details of the modelling of the recoil motion. Experimental surge results are presented, which show a number of trends in the data including an increase in surge velocity with increasing tail-beat frequency. The maximum surge velocity obtainable from the vehicle before actuator saturation occurred was 0.18 m/s, which was achieved at a tail-beat frequency 0.61 Hz and a nominal tail-beat amplitude 0.15 m. From the surge data collected, the relationship between tail-beat frequency and surge velocity appeared to be linear. The range of surge velocities obtained for the RoboSalmon was then compared to the swimming performance of a real Salmon, which showed that the swimming speed of the RoboSalmon obtained for a particular beat frequency was lower than that achievable by a real Salmon by around a factor of 3.2. This difference in performance is due to the mechanical nature of the RoboSalmon system. Overall, the work completed on the RoboSalmon has shown that a biomimetic fish-like propulsion system is potentially viable as a form of propulsion for an AUV. The experimental results show that the biomimetic system used on the RoboSalmon may have advantages over a conventional propeller- and rudder-based system in terms of improved propulsive efficiencies and increased vehicle manoeuvrability. Further investigation and development of this technology could lead to the development of AUVs with significantly increased efficiencies and manoeuvrability thus allowing longer and more challenging missions to be undertaken.

Optimum cost of transport provides a useful metric for comparing the total energetic requirements of marine animals and AUV. This chapter uses a system approach to explain why many AUV have a lower cost of transport than marine animals of similar size.