In this work, we describe the impact of aspect ratio ($AR$) on the performance of optimally phased, identical flapping flippers in a tandem configuration. Three-dimensional simulations are performed for seven sets of single and tandem finite foils at a moderate Reynolds number, with thrust producing, heave-to-pitch coupled kinematics. Increasing slenderness (or $AR$) is found to improve thrust coefficients and thrust augmentation but the benefits level off towards higher values of $AR$. However, the propulsive efficiency shows no significant change with increasing $AR$, while the hind foil outperforms the single by a small margin. Further analysis of the spanwise development and propagation of vortical structures allows us to gain some insights into the mechanisms of these wake interactions and provide valuable information for the design of novel biomimetic propulsion systems.

Pulsatile jet propulsion is a highly energy-efficient swimming mode used by various species of aquatic animals that continues to inspire engineers of underwater vehicles. Here, we present a bio-inspired jet propulsor that combines the flexible hull of a jellyfish with the compression motion of a scallop to create individual vortex rings for thrust generation. Similar to the biological jetters, our propulsor generates a nonlinear time-varying exit velocity profile and has a finite volume capacity. The formation process of the vortices generated by this jet profile is analysed using time-resolved velocity field measurements. The transient development of the vortex properties is characterised based on the evolution of ridges in the finite-time Lyapunov exponent field and on local extrema in the pressure field derived from the velocity data. Special attention is directed toward the vortex merging observed in the trailing shear layer. During vortex merging, the Lagrangian vortex boundaries first contract in the streamwise direction before expanding in the normal direction to keep the non-dimensional energy at its minimum value, in agreement with the Kelvin–Benjamin variational principle. The circulation, diameter and translational velocity of the vortex increase due to merging. The vortex merging takes place because the velocity of the trailing vortex is higher than the velocity of the main vortex ring prior to merging. The comparison of the temporal evolution of the Lagrangian vortex boundaries and the pressure-based vortex delimiters confirms that features in the pressure field serve as accurate and robust observables for the vortex formation process.

Pockmarks are sea-floor depressions that form when gas or liquid escapes from underlying sediments. Although they are a common feature of both glaciated and lower-latitude continental shelves, pockmarks have not been reported previously from the north-east Antarctic Peninsula margin. Here we use high-resolution geophysical data acquired using autonomous underwater vehicles to map > 240 pockmarks in three locations along the north-east Antarctic Peninsula shelf. The pockmarks are 0.4–45 m wide and 0.1–2.5 m deep, encompassing both smaller unit-pockmarks and larger normal-pockmarks. The high resolution of our data enables the identification of subdued features associated with the pockmarks, including acoustic flares within the water column, ejecta rims, intra-pockmark blocks and possibly even biological structures. The overprinting of subglacial and ice-marginal landforms by the pockmarks constrains their timing of formation to the last ~11 ka. The high density of pockmarks within the surveyed areas, together with geophysical evidence for the active seepage of gas to the sea floor, suggests that the expulsion of subsurface fluids is a widespread process on the north-east Antarctic Peninsula shelf that could have important implications for benthic biodiversity and the global carbon cycle.

For the path planning of autonomous underwater vehicles (AUVs) in the ocean environment, in addition to the planned path length and safe obstacle avoidance, it is also necessary to pay attention to the impact of ocean currents on the planned path. Therefore, this paper improves the original D* algorithm, and adds the obstacle cost item and the steering angle cost item as constraints on the basis of the original cost function, thus ensuring the navigation safety of the AUV. Considering that ocean currents have a greater impact on the energy consumption of AUVs, this paper establishes a cost model for the impact of ocean currents on AUV energy consumption and applies it to the D* path planning algorithm, so that AUVs can use ocean currents to reduce energy consumption, which can be seen through simulation experiments. The simulation results show that the improvement of the algorithm can plan an optimal energy consumption path.

The paper reports on a new multi-view algorithm that combines information from multiple images of a single target object, captured at different distances, to determine the identity of an object. Due to the use of global feature descriptors, the method does not involve image segmentation. The performance of the algorithm has been evaluated on a binary classification problem for a data set consisting of a series of underwater images.

The trajectory tracking of Autonomous Underwater Vehicles (AUV) is an important research topic. However, in the traditional research into AUV trajectory tracking control, the AUV often follows human-set trajectories without obstacles, and trajectory planning and tracking are separated. Focusing on this separation, a trajectory re-planning controller based on Model Predictive Control (MPC) is designed and added into the trajectory tracking controller to form a new control system. Firstly, an obstacle avoidance function is set up for the design of an MPC trajectory re-planning controller, so that the re-planned trajectory produced by the re-planning controller can avoid obstacles. Then, the tracking controller in the MPC receives the re-planned trajectory and obtains the optimal tracking control law after calculating the object function with a Sequential Quadratic Programming (SQP) optimisation algorithm. Lastly, in a backstepping algorithm, the speed jump can be sharp while the MPC tracking controller can solve the speed jump problem. Simulation results of different obstacles and trajectories demonstrate the efficiency of the proposed MPC trajectory re-planning tracking control algorithm for AUVs.

Most of the previous works on the motion control of autonomous underwater vehicles (AUVs) assume that (i) the vehicle actuators are able to tolerate every level of the control signals, and (ii) the vehicle is equipped with the velocity sensors in all degrees of freedom. These assumptions are not desirable in practice. Toward this end, this paper addresses the trajectory tracking control of the underactuated AUVs with the limited torque, without the velocity measurements and under environmental disturbances in a three-dimensional space. At first, a variable transformation is introduced which helps us to derive a second-order dynamic model for underactuated AUVs. Then, a saturated tracking controller is proposed by employing the saturation functions to bound the closed-loop error variables. This technique reduces the risk of the actuators saturation by decreasing the amplitude of the generated control signals. In addition, a nonlinear saturated observer is introduced to remove the velocity sensors from the control system. The proposed controller copes with the uncertain vehicle parameters, and constant or time-varying environmental disturbances induced by the waves and ocean currents. Lyapunov's direct method is used to show the semi-global uniform ultimate boundedness of the tracking and state estimation errors. Finally, some simulation results illustrate the effectiveness of the proposed controller.

In this paper, for the over-actuated Autonomous Underwater Vehicle (AUV) system, a novel tracking controller with thruster fault accommodation is proposed. Firstly, a cascaded control method is proposed for AUV robust tracking control. Then, we deal with the tracking control problem when one or more thrusters are completely or partly malfunctioning. Different control strategies are used to reallocate the thruster forces. For the cases that thrusters are partly malfunctioning, a weighted pseudo-inverse is firstly used to generate the normalised thruster forces. When the normalised thruster forces are out of maximum limits, the Quantum-behaviour Particle Swarm Optimisation (QPSO) is used for the restricted usage of the faulty thruster and to find the solution of the control reallocation problem within the limits. Compared with the weighted pseudo-inverse method, the QPSO algorithm does not need truncation or scaling to ensure the feasibility of the solution due to its particle search in the feasible solution space. The proposed controller is implemented in order to evaluate its performance in different faulty situations and its efficiency is demonstrated through simulation results.

Software engineering plays a key role in state-of-the-art robotics where more effective and efficient software development solutions are needed for implementation and integration of advanced robotics capabilities. Component-based software engineering and model-driven software development are two paradigms suitable to deal with such challenges. This paper presents the analysis, design, and implementation of control software for an Autonomous Underwater Vehicle (AUV). The software development stages are carried out by using a model-driven toolchain that provides support to design and build component-based software for robotics applications. A case study of a high-performance AUV control application and experimental results from a software schedulability analysis are presented.

This paper focuses on behavior recognition in an underwater application as a substitute for communicating through acoustic transmissions, which can be unreliable. The importance of this work is that sensor information regarding other agents can be leveraged to perform behavior recognition, which is activity recognition of robots performing specific programmed behaviors, and task-assignment. This work illustrates the use of Behavior Histograms, Hidden Markov Models (HMMs), and Conditional Random Fields (CRFs) to perform behavior recognition. We present challenges associated with using each behavior recognition technique along with results on individually selected test trajectories, from simulated and real sonar data, and real-time recognition through a simulated mission.

This paper focuses on the mechanism design of a slide-block structure and its application on a biomimetic modular robotic fish for three-dimensional swimming. First, as a barycenter-adjustor, the slide-block structure is integrated into a mechanical design of a robotic fish, which is constructed by a control module, a driving module, and a fan-shaped caudal fin. The three-dimensional locomotion of robotic fish is decomposed into two-dimensional locomotion in horizontal plane and ascent–descent locomotion in vertical plane. Both the kinematics of the horizontal swim and the dynamics of the ascent–descent swim are analyzed by the curve fitting method. Finally, experimental results validate the three-dimensional swimming capability of the robotic fish. Furthermore, the impact of two design parameters on the swimming capability of the robotic fish is discussed by the experimental method. The experimental results confirm that the robotic fish with one driving module and a fan-shaped low-aspect-ratio caudal foil can produce higher propulsive speed than other parameter combinations.

A novel ostraciiform swimming, vision-based autonomous robotic fish is developed in this paper. Its feasibility and capability are shown by implementing a dynamic target following task in a swimming pool. Inspired by boxfish that is highly stable and fairly maneuverable, the robotic fish is designed and constructed by locating multiple propulsors peripherally around a rigid body. Swimming locomotion of the robotic fish is achieved through harmonic oscillations of the tail and pectoral fins. The forces and moments acting on the fins and body are analyzed and the governing motion equations are derived. Through coordinating the movements of the propulsors, several typical swimming patters are empirical designed and realized. A digital camera is integrated in the robotic fish, and the visual information is processed with the embedded microcontroller. To treat the degradation of underwater image, a continuously adaptive mean shift (Camshift) algorithm is modified to keep visual lock on the moving target. A fuzzy logic controller is designed for motion regulation of a hybrid swimming pattern, which employs synchronized pectoral fins for thrust generation and tail fin for steering. A simple target following task is designed via an autonomous robotic fish swimming after a manually controlled robotic fish with fixed distance. The swimming performance of the robotic fish is tested and the effectiveness of the proposed target following method is verified experimentally.