Virtual Ship Research Articles

APF-based intelligent navigation approach for USV in presence of mixed potential directions: Guidance and control design

This paper investigates the real-time intelligent navigation approach for unmanned surface vehicle (USV), considering constraints of the randomly moving target and multiple static or moving obstacles. In the scheme, an intelligent guidance principle is developed by employing the traditional dynamic virtual ship (DVS) structure and the artificial potential field (APF) technique. The improved design for repulsive potential field can guarantee the reasonable obstacle avoidance capability. Especially, the amended repulsive terms are derived by the velocity and orientation factors of moving obstacles. Combining with the APF-based guidance, the robust neural path following control algorithm is proposed by employing the minimal learning parameter (MLP) and the nonlinear disturbance observer (DOB) technique. For merit of the improved design of DOB, the attitude of USV can be effectively stabilized to that of virtual ship. That can derive the state-of-art trade-off between the complicated control law and the hardware computing burden. Through the Lyapunov synthesis, all states of USV are with the semi-globally uniform ultimate bounded (SGUUB) stability. Two experiments have been illustrated to verify the obstacle avoidance and dynamic tracking performance of the proposed strategy.

Task strategy optimization for multi-state system based on virtual ship

The task success ratio of the complex system in the coworking situation is studied. In the existing task strategy, the equipment fault during the subsequent task is underestimated, resulting in unreasonable task progress and prone to task failure. A new strategy that takes into account subsequent faults is proposed for this problem. A concept of the virtual ship is introduced by digital simulation with the background of a navy vessel's sailing task. The new strategy is used for real-time fault prediction of complex task systems and dynamic optimization of the remaining task processes. A group of deviation coefficients is defined. With the coefficients, the new strategy is compared to the existing one. The results show that the new strategy improves the task success ratio at the cost of speed stability. After changing the task parameters, it is found that this new strategy can reduce not arriving ratio and thus improve the task success ratio when the task redundancy time coefficient is low; And when the redundancy time coefficient is extremely high or low, the difference between the two strategies is small. In sensitivity analysis, the influence of changing equipment reliability parameters on task success ratio in different strategies is investigated.

Tracking control of ship at sea based on MPC with virtual ship bunch under Frenet frame

This note focuses on the waypoints-based path following control of underactuated surface vehicles (USV) with the mechanism of static or slow time-varying obstacles avoidance at sea. In order to track curved path while avoiding obstacles, a virtual ship bunch (VSB) method is proposed based on Frenet frame with route optimization and motion limitations. To serve the need of VSB, path curve is parameterized via event triggered online fitting. Through model predictive control (MPC), the planned motion is tracked and optimized under constraints, while stability is guaranteed by Lyapunov theorem. Compared with existing researches, the VSB-MPC scheme has good robustness to model perturbation, the smoothness of manipulation is guaranteed by explicit planning under Frenet frame. Comparative experiments have been presented to demonstrate the merits of the proposed scheme.

Robust Adaptive Neural Cooperative Control for the USV-UAV Based on the LVS-LVA Guidance Principle

Around the cooperative path-following control for the underactuated surface vessel (USV) and the unmanned aerial vehicle (UAV), a logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate the reference heading signals for the USV-UAV system by using the “virtual ship” and the “virtual aircraft”, which is critical to establish an effective correlation between the USV and the UAV. Taking the steerable variables (the main engine speed and the rudder angle of the USV, and the rotor angular velocities of the UAV) as the control input, a robust adaptive neural cooperative control algorithm was designed by employing the dynamic surface control (DSC), radial basic function neural networks (RBF-NNs) and the event-triggered technique. In the proposed algorithm, the reference roll angle and pitch angle for the UAV can be calculated from the position control loop by virtue of the nonlinear decouple technique. In addition, the system uncertainties were approximated through the RBF-NNs and the transmission burden from the controller to the actuators was reduced for merits of the event-triggered technique. Thus, the derived control law is superior in terms of the concise form, low transmission burden and robustness. Furthermore, the tracking errors of the USV-UAV cooperative control system can converge to a small compact set through adjusting the designed control parameters appropriately, and it can be also guaranteed that all the signals are the semi-global uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the proposed algorithm has been verified via numerical simulations in the presence of the time-varying disturbances.

Adaptive barrier Lyapunov function-based obstacle avoidance control for an autonomous underwater vehicle with multiple static and moving obstacles

This study focuses on addressing the waypoints-based path-following problem of an autonomous underwater vehicle (AUV) within multiple static and moving obstacles environment. In order to guarantee the safety of AUV obstacle avoidance in complex marine environment, it requires an effective guidance law to plan a safe path and a robust control method to force the AUV to follow safe path to avoid obstacles. Based on the dynamical virtual ship principle, an improved guidance law is developed with the dynamic virtual AUV (DVA) principle. This guidance law generates real-time commands for AUV to follow reference path and avoid obstacle. Furthermore, by combining adaptive laws and barrier Lyapunov function, an effective robust control algorithm is proposed to drive the AUV to follow the DVA. The adaptive law is used to approximate the dynamic uncertainties and external disturbances. The barrier Lyapunov function (BLF) is employed to guarantee the tracking errors within the preset bounds and thus ensure the safety of the AUV during the obstacle avoidance process. Finally, simulations are performed to verify the effectiveness and feasibility of the proposed control strategy.

DVSL guidance-based composite neural path following control for underactuated cable-laying vessels using event-triggered inputs

In this note, the path following issue of underactuated cable-laying vessels is addressed from two aspects, i.e., guidance and control. By exploiting the hierarchical design, a so-called dual virtual ships layered (DVSL) guidance algorithm is proposed with two reference path generators. In the first guidance layer, the logical virtual ship (LVS) is used to programme the setpoints-based reference path for cables. Based on the cable-related geometrical derivation, the corresponding ship’s reference path can be obtained in the second layer, and its smoothness can be guaranteed by the adaptive virtual ship (AVS). For the control part, a novel composite neural event-triggered control algorithm is developed by taking the main engine revolution and the rudder as actual control inputs, which are characterized by the practical measurability and the aperiodic update. The radial basis function neural networks (RBF-NNs) are employed to deal with the model uncertainty, and the approximation performance is improved with the aid of the serial-parallel estimation model (SPEM). By fusing the robust neural damping technique, only two adaptive parameters require to be updated, which leads to a simpler controller with less computation burden. Besides, the inputs-dominated event-triggered mechanism is introduced to release the communication traffic in the controller-to-actuator channel. Through the Lyapunov stability analysis, all signals in the closed-loop system are guaranteed to be semi-global uniformly ultimately bounded (SGUUB), and the existence of minimum inter-event time is proved. Finally, three simulation experiments are conducted to illustrate the effectiveness and the superiority of proposed algorithm.

Measurement campaign and mathematical model construction for the ship Zodiak magnetic signature reproduction

The paper presents the partial work done within the framework of the EDA Siramis II project focused on magnetic signature reproduction of ships. Reproduction is understood here as the ability to determine the magnetic anomaly of the local Earth magnetic field in any direction and at any measurement depth due to the presence of the analysed object. The B-91 type hydrographic ship Zodiak was selected as the real case study. The work was divided into two main stages: the development of a measurement campaign taking into account physical measurements, and the development of a mathematical model on the basis of the measured values. The measurement campaign included: preparation of the measuring range, selection of equipment for the measurement of magnetic quantities and geographical location, and data recording while the ship passes the measuring point according to the designated course. As a result of the measurement campaign, magnetic flux density components were collected in different positions in relation to the measuring instruments and the ship's heading. A multi-dipole model was used to build the mathematical model in accordance with the idea of inverse modelling. The effectiveness of this model was previously checked on synthetic data of virtual ships generated using the finite element method. Experiments performed with simulation models were helpful in determining the structure of the model, the nature of the data, and the number of samples needed to properly determine the multi-dipole model parameters. The parameters were determined using the nonlinear least squares method according to the idea of data fitting. The classical Ridge and Lasso regularization methods were applied to prevent the developed multi-dipole model from overfitting. Other regularization methods based on GPS accuracy marks and modification of fitness functions were also considered. The verification was done using real data: the data generated by the model was compared with patterns recorded during the Zodiak measurement campaign. High degree of conformity of the shape of characteristics was obtained. Moreover, the correctness of model execution was confirmed by low values of quantitative indices such as RMSE and MAE representing modelling errors. The methodology presented in the paper is quite universal and can be used to determine the signatures of other ferromagnetic objects.

Path-following Control for Autonomous Navigation of Marine Vessels Considering Disturbances

Path-following control is considered as one of the most fundamental skills to realize autonomous navigation of marine vessels in the ocean. This study addresses with the path-following control for a ship in which there are environmental disturbances in the directions of the surge, sway, and yaw motions. The guiding principle and back-stepping method was utilized to solve the ship’s tracking problem on the reference path generated by a virtual ship. For path-following control, error dynamics is one of the most important skills, and it extends to the research fields of automatic collision avoidance and automatic berthing control. The algorithms for the guiding principles and error variables have been verified by numerical simulation. As a result, most error variables converged to zero values with the controller except for the yaw angle error. One of the most interesting results is that the tracking errors of path-following control between two ships are smaller than the existing safe passing distances considering interaction forces from near passing ships. Moreover, a trade-off between tracking performance and the ship’s safety should be considered for determining the proper control parameters to prevent the destructive failure of actuators such as propellers, fins, and rudders during the path-following of marine vessels.

LVS guidance principle and adaptive neural fault-tolerant formation control for underactuated vehicles with the event-triggered input

This paper presents a novel adaptive neural event-triggered formation control strategy for underactuated surface vehicles (USVs) in the presence of marine practical constraints, i.e. the waypoints-based planned path and actuator failures. The proposed strategy is composed of the guidance model and the control one. For the guidance part, the logic virtual ship (LVS) guidance principle is developed to implement the reference path programming for the formation pattern. For merit of the adaptive virtual ship, the smooth reference can be produced for followers without using the velocity information of leader. Furthermore, the proposed adaptive neural fault-tolerant control algorithm is to guarantee that the followers can maintain their pattern and converge to the corresponding reference path. In the algorithm, the neural networks (NNs)-based observer is designed to estimate the unmeasurable velocities of followers online. With the input event-triggered mechanism, two adaptive parameters are derived to compensate for the gain uncertainty and actuator failure. And that could effectively reduce the communication burden for the channel from controller to actuator. The derived closed-loop system has been proved to be with the semi-global uniform ultimate bounded (SGUUB) stability. Finally, the superiority of the proposed strategy can be verified by the simulation experiments.

Study of anti-swing control of ship cranes based on time delay feedback

2 tons 3 meters ship crane as the research object, establish the complete mathematical model of ship crane, and design the time-delay feedback control algorithm to eliminate payload swing on the basis of the built mathematical model. First, a high-precision potentiometer is used to measure the in-plane and out-of-plane oscillation of the payload. Measuring devices for the rotary angle and variation amplitude angle are created, and the anti-swing control hardware system is built by the sensing unit and the High-Speed Data Acquisition hardware system. Secondly, the control software on the VB platform is developed using the time-delay feedback algorithm. Experimentally study the effect of time-delayed feedback controller on payload swing elimination, and use induction method to get the optimal control parameters of the time-delayed feedback control algorithm. At last, the AMEsim-ADAMS co-simulation platform was built to evaluate the payload sway of the ship crane under simulated working conditions. The results show that: the hardware and software systems for anti-swing control built-in the paper can give the real-time and the exact payload swing angles. The method of adding time-delay feedback control signal to the slewing operation signal can achieve better anti-swing effects than the others. At the same time, the delayed feedback control algorithm still has a nice control effect in the case of virtual ship deck motion.

StARboard & TrACTOr: Actuated Tangibles in an Educational TAR Application

We explore the potential of direct haptic interaction in a novel approach to Tangible Augmented Reality in an educational context. Employing our prototyping platform ACTO, we developed a tabletop Augmented Reality application StARboard for sailing students. In this personal viewpoint environment virtual objects, e.g., sailing ships, are physically represented by actuated micro robots. These align with virtual objects, allowing direct physical interaction with the scene. When a user tries to pick up a virtual ship, its physical robot counterpart is grabbed instead. We also developed a tracking solution TrACTOr, employing a depth sensor to allow tracking independent of the table surface. In this paper we present concept and development of StARboard and TrACTOr. We report results of our user study with 18 participants using our prototype. They show that direct haptic interaction in tabletop AR scores en-par with traditional mouse interaction on a desktop setup in usability (mean SUS = 86.7 vs. 82.9) and performance (mean RTLX = 15.0 vs. 14.8), while outperforming the mouse in factors related to learning like presence (mean 6.0 vs 3.1) and absorption (mean 5.4 vs. 4.2). It was also rated the most fun (13× vs. 0×) and most suitable for learning (9× vs. 4×).

Spatio-temporal variation in sea state parameters along virtual ship route paths

ABSTRACT The article presents a study investigating the level of variation in sea state parameters encountered by sailing ships crossing the oceans. The sea state parameters have been obtained from a reanalysis, in this case the ERA5. The study is based on the use of different interpolation schemes to compute parameters in geographical positions off the fixed grid. It is shown that the variation in sea state parameters can be significant. Consequently, in case of sailing ships, covering relatively long distances in a short time (30–60 min), it is recommended to rely on bilinear interpolation rather than nearest neighbour. The variation in the sea state parameters is, in fact, at a level which means that the normal assumption of a stationary seaway in periods up to 3 h likely is violated for ships sailing the typical service speed (15–20+ kt).

Adaptive synchronization of marine surface ships using disturbance rejection without leader velocity

This work realizes the adaptive neural disturbance rejection for the leader–follower cooperative synchronization of surface ships with model perturbations and ocean disturbances without leader velocity measurements. The virtual ship alleviates the requirements on leader ship’s velocities such that the information requirements are only position and heading on the leader ship. The adaptive neural networks approximate model perturbations. The robustifying term attenuates neural network approximation errors. The adaptive neural network-based disturbance observer achieves the disturbance rejection which is integrated with the dynamic surface control technique. The supply ship synchronization control system is ensured to be practical stable. The synchronization control realizes the ship’s cooperative synchronization navigation. Simulations with comparisons validate the synchronization scheme.

Profiling of cybersickness and balance disturbance induced by virtual ship motion immersion combined with galvanic vestibular stimulation

Profile of cybersickness and balance disturbance induced by virtual ship motion alone and in combination with galvanic vestibular stimulation (GVS) remained unclear. Subjects were exposed to a ship deck vision scene under simulated Degree 5 or 3 sea condition using a head-mounted virtual reality display with or without GVS. Virtual ship motion at Degree 5 induced significant cybersickness with symptom profile: nausea syndrome > central (headache and dizziness) > peripheral (cold sweating) > increased salivation. During a single session of virtual ship motion exposure, GVS aggravated balance disturbance but did not affect most cybersickness symptoms except cold sweating. Repeated exposure induced cybersickness habituation which was delayed by GVS, while the temporal change of balance disturbance was unaffected. These results suggested that vestibular inputs play different roles in cybersickness and balance disturbance during virtual reality exposure. GVS might not serve as a potential countermeasure against cybersickness induced by virtual ship motion.

COLREGs-Constrained Adaptive Fuzzy Event-Triggered Control for Underactuated Surface Vessels With the Actuator Failures

This article investigates the adaptive fuzzy event-triggered control for the underactuated surface vessels (USVs), considering constraints of the International Regulations for Preventing Collisions at Sea (COLREGs) and the actuator failures. The proposed scheme can be divided into the guidance module and the control module. An improved logic virtual ship guidance principle, considering the ship-to-ship collision avoidance, is developed to generate the real-time reference signal for USVs. The main characteristic of the guidance principle is to ensure USVs sailing in the path following mode and collision avoidance mode. Especially for the collision avoidance mode, the collision avoidance guidance is targetedly designed for three sailing situations (the head-on situation, the overtaking situation, and the crossing situation), which is consistent with the COLREGs. Furthermore, an adaptive fuzzy event-triggered law is designed to control the USVs to converge to the desired path. The model unknown terms and the basic fault of the actuator are identified by the fuzzy logic system, and the fuzzy logic state observer is designed to estimate the unmeasured states of the USVs. Unlike the existing results, the communication burden from the controller to the actuators is reduced for the merits of the input event-triggered rule. Through the Lyapunov theory, it is proved that all the signals of the closed-loop control system are the semiglobal uniform ultimate bounded. Finally, the simulated examples are provided to illustrate the validity of the proposed control approach.

Event-triggered robust neural control for unmanned sail-assisted vehicles subject to actuator failures

This note focus on the waypoints-based path-following control for the unmanned sail-assisted vehicles (USAV), aiming to release the constraints of the actuator failures and gain uncertainties. The proposed scheme is formulated as two components, i.e., the composite guidance part and the control part. By utilizing the sign self-selection algorithm, the composite Logic Virtual Ship (LVS) guidance law is developed in the scheme to program the real-time heading angle for the USAV. The main superiorities of this design are to ensure the USAV navigating efficiently and choose the corresponding sailing mode: upwind mode, downwind mode or crosswind mode. Furthermore, to improve the effectiveness of the closed-loop control system, an event-triggered robust neural control algorithm is targetly designed for the rudder actuator and the sail actuator by fusing the robust neural damping technique and the input event-triggered mechanism. In this algorithm, the unknown terms of the system are tackled requiring no information of the system model and the external disturbances. The transmission burden from the controller to the actuator is reduced. And the unknown actuator failures and the gain uncertainties are compensated through four adaptive updated parameters. Based on the Lyapunov analysis, sufficient effort has been made to guarantee that all the signals of the closed-loop control system are the semi-global uniform ultimate bounded (SGUUB). Finally, the simulated results demonstrate the validity of the proposed control strategy.

Artificial forces for virtual autonomous ships with encountering situations in restricted waters

ABSTRACT Even if the same two ships operate in the same encountering situation, the actual strategies and timing of operations may be different. Therefore, the fixed collision avoidance trajectory and ship movements are no longer suitable for simulating the real ship behaviour. This paper tries to develop an artificial intelligent system that fully sensitive to the local circumstances and command a ship in virtual environment. Based on AIS (Automatic Identification System) data, this study has developed artificial forces which help decision makings on-board independently under different situations and catching the stochastic nature of ship behaviours during collision avoidances manoeuvring. Actual ship tracks are helpful for ascertaining the parameters that contribute to artificial forces in collision avoidances, while the correlation coefficient analysis is helpful to distinguish the parameters. This study will help to develop a navigation traffic simulation to reflect the realistic ship behaviour and provide reliable information for port and waterway planning, risk analysis, and mitigation measures. The method can be used in developing algorithms for autonomous ships. The method introduced in this study lays a foundation for developing artificial forces at intersections or bends, although the model is only applicable in straight channels at the moment.

Improved composite learning path-following control for the underactuated cable-laying ship via the double layers logical guidance

This paper investigates the setpoints-based path-following issue of the underactuated cable-laying ship in the presence of the model uncertainty and unknown external disturbance. To implement the cable-laying task automatically, a novel double layers logical (DLL) guidance algorithm is proposed to generate the reasonable reference path for the cable and cable-laying vessel. In the first guidance layer, the reference path of the cable is programmed automatically by applying the logical guidance law. The path programming process is based on the given setpoints information and could be in accordance with the practical cable-laying requirement. Furthermore, the desired trajectory of the ship is derived in the second one by constructing the cable-related correlation equation. As for the control part, the improved composite learning algorithm is proposed to stabilize the error dynamics between the virtual ship and the actual ship. For merits of the robust neural damping technique, only two adaptive parameters are required to be updated online. That can lead to the computation superiority, which is significant for applying the proposed algorithm in the industrial process computer. The concise design could guarantee the ease-to-implementation of the theoretical algorithm in the practical engineering. Finally, much effort has been made to ensure that all signals in the closed-loop system are semi-global uniformly ultimately bounded (SGUUB). The numerical experiments are carried out to verify the effectiveness and superiority of the proposed algorithm, including the comparative experiment and the cable-laying experiment under the simulated ocean disturbance.

Design and exploration of virtual marine ship engine room system based on Unity3D platform

Design and exploration of virtual marine ship engine room system based on Unity3D platform

Research of Virtual Ship Fire-fighting Training System Based on Virtual Reality Technique

For ocean-going ships, safety is very important. And fire would be the brunt of ship disasters and accidents. So fire emergency training is a priority. The virtual ship fire-fighting training system based on virtual reality technique plays an important role on training.