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Maritime autonomous surface ships (MASSs) have received increased attention in both academic research and industrial applications in the global shipping and shipbuilding industry in recent years. According to its definition, a MASS can independently operate without human interaction. This brings the problem of how to test and evaluate the capabilities of the autonomous navigation control system developed for MASS. This paper proposes the novel concept of a variable stability ship and the design of its control system. A variable stability ship consists of a model-scaled ship, a model-following controller, and a hardware and software platform to implement its functions. The variable stability ship can replicate the dynamic responses of different reference ships despite their dissimilarities in physical parameters and hydrodynamic characteristics with the design of the model-following controller. Therefore, it can be used to test the performance of different control strategies on various ship types such that the R&D costs of physical model-based tests can be reduced, as well as shortening the time spent in developing physical ship models. Preliminary simulations are carried out to show its effectiveness and applicability. [ABSTRACT FROM AUTHOR]

As a new VR multimedia format, Light Field (LF) has received more and more attention. LF can support users to move freely within a certain range during the experience. However, the limitation of LF acquisition technology has become the main obstacle to its large‐scale application. Since the current hardware technology cannot produce a lens small enough to meet the needs of LF capture, the intensity of the collected LF image is usually insufficient. Although there are many software LF reconstruction algorithms have been proposed to make captured result denser, they all face the problem of poor generalization in the application process. In this work, it is attempted to locate the factors that affect the performance of LF reconstruction from both the angular and spatial domains. The analysis results show that it is affected not only by the edge and texture of the LF content in the spatial domain, but also by the adjacent disparity and the reflection characteristics in the angular domain. An indicator to quantify the impact of these factors on reconstruction performance is also proposed, which will be helpful to design a new generalized adaptive LF reconstruction algorithm in the future. [ABSTRACT FROM AUTHOR]

Maritime collisions are a leading cause of accidents at sea, causing severe casualties, economic losses, and environmental damage. Although numerous methods have been developed to mitigate collisions, existing research primarily emphasises decision-making and path planning, often overlooking motion planning methods that incorporate dynamic constraints and ship-specific kinematics. This paper presents a motion planning method that takes into account ship dynamics to minimise jerk, the acceleration change rate, during ship acceleration and deceleration. The paper demonstrates the differential flatness property of the 3-DOF ship motion model, which allows for the direct use of flat outputs to implement motion planning and facilitate the addition of dynamic constraints. The front-end path search is performed using the traditional A* algorithm. To represent the trajectory as a piecewise Bézier curve, we use the Bernstein polynomial basis function. Based on this curve, we propose a motion planning method that employs jerk as the cost function and includes necessary constraints. This transforms the problem into a typical convex quadratic programming problem, ensuring the solvability of the optimisation problem. Finally, simulations are carried out to evaluate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Autonomous navigation is critical to the development of next-generation shipping systems. The proposal of intelligent ships enables innovation in the shipping and shipbuilding industry and increases the safety and efficiency of ship operations. Autonomous control of surface ships to follow a prescribed trajectory is critical in a variety of maritime applications. This paper proposes a trajectory tracking control strategy for autonomous surface ships that combines nonparametric modelling using Gaussian Process Regression (GPR) with the Model Predictive Control (MPC) framework. A Bézier curve-based Virtual Ship(BVS) guidance strategy is proposed to convert dynamic trajectory points into reference heading angles and speeds, such that the trajectory tracking problem can be decomposed into heading control and speed control problems. Gaussian process regression is utilised to identify the correlation between propeller revolution speed and ship speed, as well as the correlation between rudder angle and heading angle based on experimental data. Two GPR models are therefore constructed as the prediction models for designing MPC controllers for heading control and speed control, respectively. Nonlinear optimisation algorithms are utilised to search for optimal control commands in each sampling interval to solve the optimisation problem in MPC with GPR models and input constraints. Simulations are carried out to evaluate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]