The range of physiological adaptations possessed by marine animals allowing them to successfully operate in the marine environment is a plentiful source of inspiration for the designers of Autonomous Underwater Vehicles. This chapter compares the total energetic cost of straight line swimming for both marine animals and AUVs, using cost of transport (COT) as a comparative metric. COT is a normalised measure of the energetic cost of transporting the animal's or vehicle's mass over a unit distance. It includes non propulsion power requirements as well as considering the energy lost by actuators and mechanical couplings and energy lost in the wake. Comparisons presented in this chapter show that marine animals typically have higher optimum COT than engineered systems of equivalent size. However parallels may be drawn, for example, to increase range both marine animals and AUVs appear to favour reducing non-propulsion power costs and travelling slowly to ensure operating at the minimum COT.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence Newcastle University ePrints -eprint.ncl.ac.uk Li C, Atlar M, Haroutunian M, Anderson C, Turkmen S. An experimental investigation into the effect of Cu2O particle size on antifouling roughness and hydrodynamic characteristics by using a turbulent flow channel. Ocean Engineering 2018

Underwater navigation presents crucial issues because of the rapid attenuation of electronic magnetic waves. The conventional underwater navigation methods are achieved by acoustic equipment, such as the ultra-short-baseline localisation systems and Doppler velocity logs, etc. However, they suffer from low fresh rate, low bandwidth, environmental disturbance and high cost. In the paper, a novel underwater visual navigation is investigated based on the multiple ArUco markers. Unlike other underwater navigation approaches based on the artificial markers, the noise model of the pose estimation of a single marker and an optimal algorithm of the multiple markers are developed to increase the precision of the method. The experimental tests are conducted in the towing tank. The results show that the proposed method is able to localise the underwater vehicle accurately.

Underwater navigation is always a challenging problem, because of electromagnetic attenuation. The traditional methods involve beacons, inertial sensors, and Doppler Velocity Log (DVL), but they have many shortcomings, such as high cost, and lengthy setup time. In order to solve underwater navigation problems at low cost, an integrated visual odometry system has been developed and discussed in this paper. In this method, two inertial sensors provide acceleration and attitude of the vehicle, and an underwater sonar is used to provide the distance between the vehicle and the seabed, whilst in the visual odometry section, an optical flow algorithm has been applied for tracking feature points. With the depth provided by the sonar, 3D position of feature points can be calculated. Linear motion of the vehicle is then predicted through these feature points in dual frames. Finally, nonlinear optimization is used to correct the attitude of the vehicle using visual information. In the proposed algorithm, the vehicle trajectory can be estimated in absolute scale by using a single camera; computational complexity is reduced dramatically compared to other visual odometry methodologies; and this algorithm allows the approach to work in sparse texture conditions. The results from practical experiments demonstrate that the method is effective and it is also a low-cost solution.