SearcharxivSearch

arXiv subjects

Atsuo Maki

Publications and source records attributed to Atsuo Maki.

At least 19 recordsLinked to original sources

Development and Identification of a Linear Low-Speed Ship Maneuvering Model from Full-Scale Data

Despite significant technological progress, the realization of fully autonomous berthing and unberthing remains a significant challenge. One of the primary obstacles is the complex, non-linear nature of low-speed ship dynamics, which are difficult to model and control and often necessitate equally complex maneuvering models and control systems. This study proposes a simplified approach to bridge this gap by modeling the ship dynamics in the form of a time-invariant, continuous-time linear state-space system. The model parameters are estimated through system identification using the Covariance Adaptation Strategy Evolution Strategy (CMA-ES) applied to full-scale maneuvering data. Validation results demonstrate a strong agreement between the model output and empirical data. This outcome demonstrates the significant potential of simplified models to effectively define the maneuvering motion of a ship at low speeds.

eess.SY

Probabilistic Prediction of Ship Maneuvering Motion using Ensemble Learning with Feedforward Neural Networks

In the field of Maritime Autonomous Surface Ships (MASS), the accurate modeling of ship maneuvering motion for harbor maneuvers is a crucial technology. Non-parametric system identification (SI) methods, which do not require prior knowledge of the target ship, have the potential to produce accurate maneuvering models using observed data. However, the modeling accuracy significantly depends on the distribution of the available data. To address these issues, we propose a probabilistic prediction method of maneuvering motion that incorporates ensemble learning into a non-parametric SI using feedforward neural networks. This approach captures the epistemic uncertainty caused by insufficient or unevenly distributed data. In this paper, we show the prediction accuracy and uncertainty prediction results for various unknown scenarios, including port navigation, zigzag, turning, and random control maneuvers, assuming that only port navigation data is available. Furthermore, this paper demonstrates the utility of the proposed method as a maneuvering simulator for assessing heading-keeping PD control. As a result, it was confirmed that the proposed method can achieve high accuracy if training data with similar state distributions is provided, and that it can also predict high uncertainty for states that deviate from the training data distribution. In the performance evaluation of PD control, it was confirmed that considering worst-case scenarios reduces the possibility of overestimating performance compared to the true system. Finally, we show the results of applying the proposed method to full-scale ship data, demonstrating its applicability to full-scale ships.

eess.SY

Data Augmentation Methods of Dynamic Model Identification for Harbor Maneuvers using Feedforward Neural Network

A dynamic model for an automatic berthing and unberthing controller has to estimate harbor maneuvers, which include berthing, unberthing, approach maneuvers to berths, and entering and leaving the port. When the dynamic model is estimated by the system identification, a large number of tests or trials are required to measure the various motions of harbor maneuvers. However, the amount of data that can be obtained is limited due to the high costs and time-consuming nature of full-scale ship trials. In this paper, we improve the generalization performance of the dynamic model for the automatic berthing and unberthing controller by introducing data augmentation. This study used slicing and jittering as data augmentation methods and confirmed their effectiveness by numerical experiments using the free-running model tests. The dynamic model is represented by a neural network-based model in numerical experiments. Results of numerical experiments demonstrated that slicing and jittering are effective data augmentation methods but could not improve generalization performance for extrapolation states of the original dataset.

eess.SY

On Neural Network Identification for Low-Speed Ship Maneuvering Model

Several studies on ship maneuvering models have been conducted using captive model tests or computational fluid dynamics (CFD) and physical models, such as the maneuvering modeling group (MMG) model. A new system identification method for generating a low-speed maneuvering model using recurrent neural networks (RNNs) and free running model tests is proposed in this study. We especially focus on a low-speed maneuver such as the final phase in berthing to achieve automatic berthing control. Accurate dynamic modeling with minimum modeling error is highly desired to establish a model-based control system. We propose a new loss function that reduces the effect of the noise included in the training data. Besides, we revealed the following facts - an RNN that ignores the memory before a certain time improved the prediction accuracy compared with the "standard" RNN, and the random maneuver test was effective in obtaining an accurate berthing maneuver model. In addition, several low-speed free running model tests were performed for the scale model of the M.V. Esso Osaka. As a result, this paper showed that the proposed method using a neural network model could accurately represent low-speed maneuvering motions.

eess.SY

Collision probability reduction method for tracking control in automatic docking / berthing using reinforcement learning

Automation of berthing maneuvers in shipping is a pressing issue as the berthing maneuver is one of the most stressful tasks seafarers undertake. Berthing control problems are often tackled via tracking a predefined trajectory or path. Maintaining a tracking error of zero under an uncertain environment is impossible; the tracking controller is nonetheless required to bring vessels close to desired berths. The tracking controller must prioritize the avoidance of tracking errors that may cause collisions with obstacles. This paper proposes a training method based on reinforcement learning for a trajectory tracking controller that reduces the probability of collisions with static obstacles. Via numerical simulations, we show that the proposed method reduces the probability of collisions during berthing maneuvers. Furthermore, this paper shows the tracking performance in a model experiment.

eess.SY

Conceptual Design on the Field of View of Celestial Navigation Systems for Maritime Autonomous Surface Ships

In order to understand the appropriate field of view (FOV) size of celestial automatic navigation systems for surface ships, we investigate the variations of measurement accuracy of star position and probability of successful star identification with respect to FOV, focusing on the decreasing number of observable star magnitudes and the presence of physically covered stars in marine environments. The results revealed that, although a larger FOV reduces the measurement accuracy of star positions, it increases the number of observable objects and thus improves the probability of star identification using subgraph isomorphism-based methods. It was also found that, although at least four objects need to be observed for accurate identification, four objects may not be sufficient for wider FOVs. On the other hand, from the point of view of celestial navigation systems, a decrease in the measurement accuracy leads to a decrease in positioning accuracy. Therefore, it was found that maximizing the FOV is required for celestial automatic navigation systems as long as the desired positioning accuracy can be ensured. Furthermore, it was found that algorithms incorporating more than four observed celestial objects are required to achieve highly accurate star identification over a wider FOV.

cs.RO

Quantitative Evaluation of Full-Scale Ship Maneuvering Characteristics During Berthing and Unberthing

Leveraging empirical data is crucial in the development of accurate and reliable virtual models for the advancement of autonomous ship technologies and the optimization of port operations. This study presents an in-depth analysis of ship berthing and unberthing maneuvering characteristics by utilizing a comprehensive dataset encompassing the operation of a full-scale ship in diverse infrastructural and environmental conditions. Various statistical techniques and time-series analysis were employed to process and interpret the operational data. A systematic analysis was conducted on key performance variables, including approach speed, drift angles, turning motions, distance from obstacles, and actuator utilization. The results demonstrate significant discrepancies between the empirical data and the established maneuvering characteristics. These findings have the potential to significantly enhance the accuracy and reliability of conventional maneuvering models, such as the Mathematical Modeling Group (MMG) model, and improve the conditions used in captive model tests for the identification of maneuvering model parameters. Furthermore, these findings could inform the development of more robust autonomous berthing and unberthing algorithms and digital twins.

eess.SY

Perspective on the Marine Simulator for Autonomous Vessel Development

There is a growing demand for simulators for the research and development of maritime autonomous surface ships (MASS) and the approval of autonomous navigation algorithms. Simulators are used for purposes such as evaluation and training and are taken on various configurations accordingly. The ship maneuvering mathematical model used in such a simulator is an important element that characterizes the simulator. In this paper, we discuss the dynamic model of the hull and its position in the simulator that will be required for MASSs in the future. It also discusses guidelines for selecting an appropriate model, which has not been discussed extensively in previous studies. Finally, we discuss the functional requirements that simulators should have.

eess.SY

Simultaneous optimization of control gains and reference filter coefficients for trajectory tracking control

Research on vessel automation and autonomy is currently being conducted by various countries and institutions. Safe and accurate ship control algorithms are crucial to realize automated operation. Actuator drive constraints of a target ship may jeopardize the stability of the control law and require complex theory. In this study, we include a penalty term to the control law gain optimization stage of dynamic positioning systems to account for the amounts by which the actuator input value and its rate of change exceed the constraint. The parameters for generating a suitable reference path for the control law are identified simultaneously with the control gains. The simulation results show that the proposed method can realize control parameters and a reference design with excellent tracking performance while determining the cost of the controller design by considering the effects of both the actuators and rate saturation.

math.OC

Validation of Theoretical Estimation Methods and Maximum Value Distribution Calculation for Parametric Roll Amplitude in Long-Crested Irregular Waves

Parametric rolling is a parametric excitation phenomenon caused by GM variation in waves. There are a lot of studies of the estimation the conditions, the occurrence, and the amplitude of parametric rolling. On the other hand, there are relatively few cases in which theoretical methods for estimating parametric roll amplitudes in irregular waves have been validated in tank tests. The primary objective of this study is to validate theoretical estimation methods for the parametric roll amplitude in irregular waves and improve their accuracy. First, the probability density functions (PDF) of the parametric roll amplitude obtained from the model ship motion experiment in irregular waves are compared with that obtained from theoretical estimation methods. Second, the method to improve the accuracy of estimation of the roll restoring variation in irregular waves is suggested. Third, the method to estimate the distribution of the maximum amplitude of parametric rolling in irregular waves. As a result, the PDFs of the roll amplitude obtained from the experiments differ from the results of theoretical estimation. After that, by correcting GM variation, the results of theoretical estimation are closer to the experimental results. Moreover, by the theoretical estimation method using the moment equation, the qualitative estimation for the PDF of the maximum roll amplitude is succeeded.

physics.flu-dyn

A Practical and Online Trajectory Planner for Autonomous Ships' Berthing, Incorporating Speed Control

Autonomous ships are essentially designed and equipped to perceive their internal and external environment and subsequently perform appropriate actions depending on the predetermined objective(s) without human intervention. Consequently, trajectory planning algorithms for autonomous berthing must consider factors such as system dynamics, ship actuators, environmental disturbances, and the safety of the ship, other ships, and port structures, among others. In this study, basing the ship dynamics on the low-speed MMG model, trajectory planning for an autonomous ship is modeled as an optimal control problem (OCP) that is transcribed into a nonlinear programming problem (NLP) using the direct multiple shooting technique. To enhance berthing safety, besides considering wind disturbances, speed control, actuators' limitations, and collision avoidance features are incorporated as constraints in the NLP, which is then solved using the Sequential Quadratic Programming (SQP) algorithm in MATLAB. Finally, the performance of the proposed planner is evaluated through (i) comparison with solutions obtained using CMA-ES for two different model ships, (ii) trajectory planning for different harbor entry and berth approach scenarios, and (iii) feasibility study using stochastically generated initial conditions and positions within the port boundaries. Simulation results indicate enhanced berthing safety as well as practical and computational feasibility making the planner suitable for real-time applications.

eess.SY

Approximate probability density function for nonlinear surging in irregular following seas

The broaching that follows the surf-riding is a dangerous phenomenon that can lead to the capsizing of a vessel due to its violent yaw motion. Most of the previous studies on surf-riding phenomena in irregular waves have been conducted by replacing irregular waves with regular waves. In contrast, this study provides suggestions on how to directly calculate nonlinear surge motion in irregular seas. In this study, the statistical aspects of the surf-riding phenomenon are first presented. Then, under several approximations, we show how to calculate the probability density function theoretically. Although the results obtained are based on strong approximations, it is found that the nonlinear surge oscillations in irregular following seas can be explained from a qualitative point of view.

math.DS

Parameter fine-tuning method for MMG model using real-scale ship data

In this paper, a fine-tuning method of the parameters in the MMG model for the real-scale ship is proposed. In the proposed method, all of the arbitrarily indicated target parameters of the MMG model are tuned simultaneously in the framework of SI using time series data of real-sale ship maneuvering motion data to steadily improve the accuracy of the MMG model. Parameter tuning is formulated as a minimization problem of the deviation of the maneuvering motion simulated with given parameters and the real-scale ship trials, and the global solution is explored using CMA-ES. By constraining the exploration ranges to the neighborhood of the previously determined parameter values, the proposed method limits the output in a realistic range. The proposed method is applied to the tuning of 12 parameters for a container ship with five different widths of the exploration range. The results show that, in all cases, the accuracy of the maneuvering simulation is improved by applying the tuned parameters to the MMG model, and the validity of the proposed parameter fine-tuning method is confirmed.

eess.SY

Review of the analytical prediction method of surf-riding threshold in following sea, and its relation to IMO second-generation intact stability criteria

In high-speed maritime operations, the broaching phenomenon can pose a significant risk when navigating in following/quartering seas. The occurrence of this phenomenon can result in a violent yaw motion, regardless of the steering effort, which, in turn, cause the resulting centrifugal force to capsize a vessel. A necessary condition for the occurrence of broaching is the surf-riding phenomenon. Therefore, the International Maritime Organization (IMO) has set up criteria to include theoretical formulas for estimating the occurrence of surf-riding phenomena. The theoretical equation used in the IMO's second-generation intact stability criteria (SGISC) to estimate the surf-riding threshold is based on Melnikov's method. This paper presents nonlinear equations describing the forward and backward motions of a ship. However, such equations cannot be directly solved; therefore, we proposed the use of and explain various approximate solution methods, including Meknikov's method. Subsequently, the relationship between the theoretical prediction method of the surf-riding threshold rooted in Melnikov's method and the IMO's SGISC is determined.

math.GM

Nonlinear steering control under input magnitude and rate constraints with exponential convergence

A ship steering control is designed for a nonlinear maneuvering model whose rudder manipulation is constrained in both magnitude and rate. In our method, the tracking problem of the target heading angle with input constraints is converted into the tracking problem for a strict-feedback system without any input constraints. To derive this system, hyperbolic tangent ($\tanh$) function and auxiliary variables are introduced to deal with the input constraints. Furthermore, using the feature of the derivative of $\tanh$ function, auxiliary systems are successfully derived in the strict-feedback form. The backstepping method is utilized to construct the feedback control law for the resulting cascade system. The proposed steering control is verified in numerical experiments, and the result shows that the tracking of the target heading angle is successful using the proposed control law.

eess.SY

Comparison of stochastic stability boundaries for parametrically forced systems with application to ship rolling motion

Numerous accidents caused by parametric rolling have been reported on container ships and pure car carriers (PCCs). A number of theoretical studies have been performed to estimate the occurrence condition of parametric rolling in both regular and irregular seas. Some studies in random wave conditions have been the approximate extension of the occurrence conditions for regular waves (e.g. Maki et al). Furthermore, several researches have been based on the stochastic process in ocean engineering (Roberts and Dostal). This study tackled the parametric rolling in irregular seas from the stability of the system's origin. It provided a novel theoretical explanation of the instability mechanism for two cases: white noise parametric excitation and colored noise parametric excitation. The authors then confirmed the usefulness of the previously provided formulae by Roberts and Dostal through numerical examples.

physics.app-ph

Covariance Matrix Adaptation Evolutionary Strategy with Worst-Case Ranking Approximation for Min--Max Optimization and its Application to Berthing Control Tasks

In this study, we consider a continuous min--max optimization problem $\min_{x \in \mathbb{X} \max_{y \in \mathbb{Y}}}f(x,y)$ whose objective function is a black-box. We propose a novel approach to minimize the worst-case objective function $F(x) = \max_{y} f(x,y)$ directly using a covariance matrix adaptation evolution strategy (CMA-ES) in which the rankings of solution candidates are approximated by our proposed worst-case ranking approximation (WRA) mechanism. We develop two variants of WRA combined with CMA-ES and approximate gradient ascent as numerical solvers for the inner maximization problem. Numerical experiments show that our proposed approach outperforms several existing approaches when the objective function is a smooth strongly convex--concave function and the interaction between $x$ and $y$ is strong. We investigate the advantages of the proposed approach for problems where the objective function is not limited to smooth strongly convex--concave functions. The effectiveness of the proposed approach is demonstrated in the robust berthing control problem with uncertainty.ngly convex--concave functions. The effectiveness of the proposed approach is demonstrated in the robust berthing control problem with uncertainty.

cs.NE

Ship trajectory planning method for reproducing human operation at ports

Among ship maneuvers, berthing/unberthing maneuvers are one of the most challenging and stressful phases for captains. Concerning burden reduction on ship operators and preventing accidents, several researches have been conducted on trajectory planning to automate berthing/unberthing. However, few studies have aimed at assisting captains in berthing/unberthing. The trajectory to be presented to the captain should be a maneuver that reproduces human captain's control characteristics. The previously proposed methods cannot explicitly reflect the motion and navigation, which human captains pay particular attention to reduce the mental burden in the trajectory planning. Herein, mild constraints to the trajectory planning method are introduced. The constraints impose certain states (position, bow heading angle, ship speed, and yaw angular velocity), to be taken approximately at any given time. The introduction of this new constraint allows imposing careful trajectory planning (e.g., in-situ turns at zero speed or a pause for safety before going astern), as if performed by a human during berthing/unberthing. The algorithm proposed herein was used to optimize the berthing/unberthing trajectories for a large car ferry. The results show that this method can generate the quantitatively equivalent trajectory recorded in the actual berthing/unberthing maneuver performed by a human captain.

cs.RO