This paper tackles the highly challenging problem of automatic berthing for autonomous surface vessels (ASVs), encompassing trajectory planning, trajectory tracking, and collision avoidance. Firstly, a novel A* algorithm integrated with a quasi-uniform B-spline and quadratic interpolation method (A*QB) is proposed for generating a smooth trajectory from the initial position to the berth, utilizing an offline-generated scaled map. Secondly, the optimal nonlinear model predictive control (NMPC)-based trajectory-tracking framework is established, incorporating the model’s uncertainty, the input saturation, and environmental disturbances, based on a 3-DOF model of a ship. Finally, considering the collision risks during port berthing, a COLREGs-based collision avoidance method is investigated. Consequently, a novel trajectory-tracking and COLREGs-based collision avoidance (TTCCA) scheme is proposed, ensuring that the ASV navigates along the desired trajectory, safely avoids both static and dynamic obstacles, and successfully reaches the berth. To validate the TTCCA approach, numerical simulations are conducted across four scenarios with comparisons to existing methods. The experimental results demonstrate the effectiveness and superiority of the proposed scheme.

In order to solve the problem that the cesium optical pump magnetometer is disturbed by the carrier’s interference magnetic field during magnetic field anomaly detection, an interference magnetic field compensation method based on an improved mayfly optimization algorithm (IMOA) was proposed in this paper. First, by combining the measurement results of the attitude sensor with the geomagnetic inclination and magnetic declination in the locality, the measurement results of the optical pump magnetometer can be decomposed into the component values under the three axes of the carrier coordinate system. A compensation model including the carrier interference magnetic field was established. Then, considering the poor global search performance that existed in the mayfly optimization algorithm (MOA), an elite chaotic reverse learning strategy and Levy mutation strategy were introduced to improve the MOA. The compensation performance of the IMOA was estimated with a series of field experiments and compared with the stretching particle swarm optimization algorithm. The experiment results indicated that these two methods can effectively compensate the magnetometer’s measurement values, and that the IMOA method more easily jumps out of the local optimum, and has higher compensation accuracy.

The horizontal thrusters located as X shape is a commonly used configuration in remotely operated underwater vehicle (ROV). To improve the motion performance of the remotely operated underwater vehicle with this configuration for some typical operation tasks, a multistep thrust allocation method based on priority idea is proposed. Firstly, the thrust allocation result of every single force/moment among the horizontal thrusters is obtained by using a piecewise calculation method. Then, a thrust allocation function of multiple forces and moment is constructed, transforming the thrust allocation problem into a multiparameter optimization problem. The objective function of the optimization problem is established based on priority idea, and limits of the thrusters are considered as constraints. Finally, a thrust redistribution method is adopted in order to further utilize the unsaturated thrusters in the propulsion system. Simulation results show that the proposed thrust allocation method has various advantages over the pseudo-inverse method, which makes the remotely operated underwater vehicle perform perfectly in the given operation task. The proposed method has important practical value and application prospects.

To improve the vertical plane motion performance of an underwater vehicle with bow and stern elevators under actuator saturation and external disturbance conditions, a new control method is proposed in this paper. Firstly, for simplifying the analysis of the coupled kinetics equation of the underwater vehicle, virtual control variables are introduced to decompose the kinetics equation into two cascaded components. Then, a framework consisting of control law and control allocation is presented according to the cascaded components. In the aspect of control law, a double closed-loop control scheme is designed. The outer loop realizes the depth control by adjusting the expected heave velocity and pitch of the underwater vehicle with an S-plane regulator and a subsection function. Meanwhile, an Augmented Linear Quadratic Regulator (ALQR) is employed in the inner loop to control the heave velocity and pitch without steady-state error. Considering the physical constraints of elevators, a pitching-priority idea is adopted in the design of the control allocation to prioritize the pitch control requirement of the underwater vehicle. Finally, based on the framework, disturbances are estimated and compensated to enhance the anti-interference performance, as well as, auxiliary functions are constructed for reducing the adverse effect caused by saturation. Simulation results show that the new control method performs perfectly under various conditions, it is also conducive to the navigation safety of the underwater vehicle because of its superior pitch control capability.

The advancement of unmanned platforms is driving the miniaturization and cost reduction of the multi-beam echosounder (MBES). In the process of MBES array calibration, the mutual coupling significantly impacts the performance of parameter estimation. We propose a correction method to mitigate the mutual coupling effects in the calibration of MBES acoustic array. Initially, a near-field focused beamforming model is established to assess the influence of mutual coupling. Subsequently, the covariance matrix in the frequency domain is constructed to enhance algorithm efficiency and simplify solution procedures. This construction eliminates the need for a low-pass filtering step after heterodyning through extracting peak values near zero frequency in the signal frequency domain. Meanwhile, the Toeplitz property is leveraged to render the estimation results independent of the mutual coupling matrix. Finally, the mutual coupling coefficients and the direction of arrival (DOA) are joint-estimated and the Cramér–Rao bound is derived. The presented method effectively addresses the engineering challenge of MBES mutual coupling calibration. Additionally, the performance of the proposed method is verified through the measured data in simulation and tank experiments.