Navigation Simulation Research Articles

Toward multimodal learning analytics in simulation-based collaborative learning: A design ethnography of maritime training

AbstractCollaborative learning in high-fidelity simulators is an important part of how master mariner students are preparing for their future career at sea by becoming part of a ship’s bridge team. This study aims to inform the design of multimodal learning analytics to be used for providing automated feedback to master mariner students engaged in collaborative learning activities in high-fidelity navigation simulators. Through a design ethnographic approach, we analyze video records of everyday training practices at a simulator center in Scandinavia, exploring (a) how feedback is delivered to students during collaborative activities in full-mission simulators and (b) which sensors are needed and why they are needed for capturing the multimodal nature of professional performance, communication, and collaboration in simulation-based collaborative learning. Our detailed analysis of two episodes from the data corpus shows how the delivery of feedback during simulations consists of recurring, multidimensional, and multimodal feedback cycles, comprising instructors’ close monitoring of student’s actions to continuously assess the fit between the learning objectives and the ongoing task. Through these embedded assessments, feedback that draws on the rich semiotic resources of the simulated environment, while considering aspects of realism and authenticity, is provided. Considering the multidimensional and multimodal nature of feedback in professional learning contexts, we identify technologies and sensors needed for capturing professional performance in simulated environments.

Design and Implementation of a Shipborne Echo Sounder Simulator Based on a Seabed Echo Scattering and Noise Model

The Manila Amendment 2010 to the STCW International Convention has made clear requirements for seafarers to use the navigation simulation system for training. A shipborne echo sounder is an important navigation aid equipment necessary for a ship’s bridge. Proper use of this equipment can effectively prevent ship grounding accidents. Given the lack of research on simulating different seabed substrate echoes within echo sounder simulations, this paper proposes an algorithm for generating echoes and clutter from various seabed substrates, based on the Jackson model and noise model. Using the seabed echo generation algorithm, the bathymetric data and seabed echo under the influence of ship rolling are generated, the seabed echo simulation of the sounder under the influence of four different grazing angles and six different substrates is realized. Clutter images, including random noise, bubble interference, co-frequency interference, and fish school interference, are also simulated. A typical ship echo sounder simulator is designed and developed. The echo sounder simulator developed in this paper has high realism in seabed echoes and clutter simulation, complete functions, and friendly human–computer interaction. The system has been used by college students and crews, with satisfactory results, which can effectively meet the needs of actual training of seafarers.

A virtual environment designed for testing location-based services based on navigation simulation in the digital twin

A virtual environment designed for testing location-based services based on navigation simulation in the digital twin

Simulation of Ship Berthing Operation at Luojing Container Terminal Under Extreme Sea Conditions

The Luojing Port Area of the Port of Shanghai, specifically the coal terminal and ore terminal, used to be the main port area for coal and ore bulk cargo transportation services in the Port of Shanghai.To enhance the container handling capacity at Shanghai port, this study conducted a series of simulation tests at Luojing Container Terminal. The tests were designed according to the terminal's specifications, taking into account the limit berthing wind direction and wind speed (levels 6 and 7). This study selected an appropriate representative ship type for the comprehensive simulation tests, and it thoroughly tested the berthing limits under various extreme conditions using an advanced navigation simulator. The experiment obtained the motion parameters and trajectory of the simulated ship. Based on these results, this study analyzed and evaluated the safety of the rotary waters and berthing operations, ensuring they met the safety assessment requirements for wharf engineering. The study examined the berthing time window, berthing mode, boundary conditions, and safety guarantee measures under extreme sea conditions at Luojing Container Terminal. Finally, By analyzing the berthing simulation trajectory diagrams, tugboat usage, and vessel maneuvering data under the eight extreme berthing conditions, this study formulated a safe berthing plan for ships.

Exploration-exploitation model of moth-inspired olfactory navigation.

Navigation of male moths towards females during the mating search offers a unique perspective on the exploration-exploitation (EE) model in decision-making. This study uses the EE model to explain male moth pheromone-driven flight paths. Wind tunnel measurements and three-dimensional tracking using infrared cameras have been leveraged to gain insights into male moth behaviour. During the experiments in the wind tunnel, disturbance to the airflow has been added and the effect of increased fluctuations on moth flights has been analysed, in the context of the proposed EE model. The exploration and exploitation phases are separated using a genetic algorithm to the experimentally obtained dataset of moth three-dimensional trajectories. First, the exploration-to-exploitation rate (EER) increases with distance from the source of the female pheromone is demonstrated, which can be explained in the context of the EE model. Furthermore, our findings reveal a compelling relationship between EER and increased flow fluctuations near the pheromone source. Using an olfactory navigation simulation and our moth-inspired navigation model, the phenomenon where male moths exhibit an enhanced EER as turbulence levels increase is explained. This research extends our understanding of optimal navigation strategies based on general biological EE models and supports the development of bioinspired navigation algorithms.

System level simulation of the winter navigation in the Baltic Sea

Efficient winter navigation has crucial importance for Finland as all Finnish harbors are icebound every winter. A winter navigation system level simulation tool has been developed to analyse the marine traffic in wintertime and to analyse the present and future need of icebreakers when both marine traffic patterns, ice-going ship characteristics and ice conditions will change. This paper summarises the basic principle of the tool and presents some recent applications together with the conducted verification and validation. The tool has been applied both in the northern part of the Baltic Sea and in the south to study the winter navigation system: on the Bay of Bothnia for Finnish marine traffic and the Gulf of Finland for Estonian marine traffic.

Research on Intelligent Navigation System Based on Aerospace Big Data Traffic System

This paper studies the navigation technology of the On-Orbit Servicing Spacecraft (OSS) and proposes an overall solution for the OSS navigation system. The composition of the OSS satellite navigation simulation system and simulation supporting environment are studied. Then a new SSUKF navigation filter is proposed based on the hyper spherical distributed feature sampling point transform algorithm (SSUT) and the non-scanning Kalman filter (UKF). The numerical simulation of the OSS system is studied based on MATLAB/RTW. Finally, the SSUKF algorithm and the conventional UKF algorithm are simulated digitally. The effectiveness and advanced nature of the hybrid Kalman filter applied to spacecraft autonomous navigation are verified.

Soft Actor-Critic and Risk Assessment-Based Reinforcement Learning Method for Ship Path Planning

Ship path planning is one of the most important themes in waterway transportation, which is deemed as the cleanest mode of transportation due to its environmentally friendly and energy-efficient nature. A path-planning method that combines the soft actor-critic (SAC) and navigation risk assessment is proposed to address ship path planning in complex water environments. Specifically, a continuous environment model is established based on the Markov decision process (MDP), which considers the characteristics of the ship path-planning problem. To enhance the algorithm’s performance, an information detection strategy for restricted navigation areas is employed to improve state space, converting absolute bearing into relative bearing. Additionally, a risk penalty based on the navigation risk assessment model is introduced to ensure path safety while imposing potential energy rewards regarding navigation distance and turning angle. Finally, experimental results obtained from a navigation simulation environment verify the robustness of the proposed method. The results also demonstrate that the proposed algorithm achieves a smaller path length and sum of turning angles with safety and fuel economy improvement compared with traditional methods such as RRT (rapidly exploring random tree) and DQN (deep Q-network).

Analysis of Transportation Systems for Colonies on Mars

The colonization of Mars poses unprecedented challenges in developing sustainable and efficient transportation systems to support inter-settlement connectivity and resource distribution. This study conducts a comprehensive evaluation of two proposed transportation systems for Martian colonies: a ground-based magnetically levitated (maglev) train and a low-orbital spaceplane. Through simulation models, we assess the energy consumption, operational and construction costs, and environmental impacts of each system. Monte Carlo simulations further provide insights into the cost variability and financial risk associated with each option over a decade. Our findings reveal that while the spaceplane system offers lower average costs and reduced financial risk, the maglev train boasts greater scalability and potential for integration with Martian infrastructural development. The maglev system, despite its higher initial cost, emerges as a strategic asset for long-term colony expansion and sustainability, highlighting the need for balanced investment in transportation technologies that align with the goals of Martian colonization. Further extending our exploration, this study introduces advanced analysis of alternative transportation technologies, including hyperloop systems, drones, and rovers, incorporating dynamic environmental modeling of Mars and reinforcement learning for autonomous navigation. In an effort to enhance the realism and complexity of our navigation simulation of Mars, we introduce several significant improvements. These enhancements focus on the inclusion of dynamic atmospheric conditions, the simulation of terrain-specific obstacles such as craters and rocks, and the introduction of a swarm intelligence approach for navigating multiple drones simultaneously. This analysis serves as a foundational framework for future research and strategic planning in Martian transportation infrastructure.

Simulation of autonomous navigation of turtlebot robot system based on robot operating system

Complex system science has recently shifted its focus to include modeling, simulation, and behavior control. An effective simulation software built on robot operating system (ROS) is used in robotics development to facilitate the smooth transition between the simulation environment and the hardware testing of control behavior. In this paper, we demonstrate how the simultaneous localization and mapping (SLAM) algorithm can be used to allow a robot to navigate autonomously. The Gazebo is used to simulate the robot, and Rviz is used to visualize the simulated data. The G-mapping package is used to create maps using collected data from a variety of sensors, including laser and odometry. To test and implement autonomous navigation, a Turtlebot was used in a Gazebo-generated simulated environment. In our opinion, additional study on ROS using these important tools might lead to a greater adoption of robotics tests performed, further evaluation automation, and efficient robotic systems.

A robust estimation method of GNSS/IMU fusion kalman filter

Aiming at the traditional gross error detection method of GNSS/IMU fusion Kalman filter, which simply retains or eliminates abnormal observation data and does not make full use of useful observation information, a new robust estimation method of Kalman filter is proposed. Based on the chi-square statistical hypothesis test, this method constructs continuous change measurement using weight coefficient, fully excavates measurable innovation between normal value and abnormal value, and establishes a new measurement update equation of Kalman filter robust estimation. Finally, through GNSS/IMU integrated navigation simulation, the advantages of the new Kalman filter are verified: no parameter adjustment is required, and the statistical error fluctuation is smaller than that of the traditional adaptive filter.

Intelligent Navigation System based on Big Data Traffic System

This paper studies the navigation technology of the On-Orbit Servicing Spacecraft (OSS) and proposes an overall solution for the OSS navigation system. The composition of the OSS satellite navigation simulation system and simulation supporting environment are studied. Then a new SSUKF navigation filter is proposed based on the hyper spherical distributed feature sampling point transform algorithm (SSUT) and the non-scanning Kalman filter (UKF). The numerical simulation of the OSS system is studied based on MATLAB/RTW. Finally, the SSUKF algorithm and the conventional UKF algorithm are simulated digitally. The effectiveness and advanced nature of the hybrid Kalman filter applied to spacecraft autonomous navigation are verified.

One-Way-Signal-Based Localization Method of Multiple Autonomous Underwater Vehicles for Distributed Ocean Surveys

This study proposes a simultaneous localization method of a group of autonomous underwater vehicles (AUVs) based on one-way signals to realize distributed oceanographic surveys. Each AUV group consists of a single high-performance AUV (parent AUV) and the other AUVs (child AUVs). The child AUVs estimate their states (position and heading) based on the parent AUV as a positioning reference. By assuming a situation in which many AUV groups are deployed, the child AUVs can receive positioning signals from multiple parent AUVs. Although only the direction information of the parent AUV can be obtained from a signal from one parent AUV, the child AUVs can estimate their states by receiving signals from different parent AUVs. Sea experiments were conducted using an autonomous buoy and an AUV. The effectiveness of the proposed method was evaluated through a navigation simulation based on the sensor data obtained from the experiments.

Global Path Planning for Autonomous Ship Navigation Considering the Practical Characteristics of the Port of Ulsan

This study introduces global path planning for autonomous ships in port environments, with a focus on the Port of Ulsan, where various environmental factors are modeled for analysis. Global path planning is considered to take place from departure to berth, specifically accounting for scenarios involving a need to navigate via anchorage areas as waypoints due to unexpected increases in port traffic or when direct access to the berth is obstructed. In this study, a navigable grid for autonomous ships was constructed using land, breakwater, and water depth data. The modeling of the Port of Ulsan’s traffic lanes and anchorage areas reflects the port’s essential maritime characteristics for global path planning. In this study, an improved A* algorithm, along with grid-based path planning, was utilized to determine a global path plan. We used smoothing algorithms to refine the global paths for practical navigation, and the validation of these paths was achieved through conducting ship maneuvering simulations from model tests, which approximate real-world navigation in navigational simulation. This approach lays the groundwork for enhanced route generation studies in complex port environments.

A method for implementing a ship navigation simulator for the generation and utilization of virtual data

Active research is underway to utilize various sensors for situational awareness, but validating these studies requires real sensor data, which is challenging to acquire due to the time and space constraints inherent in ships. Additionally, the diverse formats of sensor data and the need for postprocessing pose further hurdles. By developing a ship navigation simulator that faithfully replicates real-world environments, these limitations can be overcome, and ample virtual sensor data can be generated through immersive simulations. In this study, we propose a method for implementing such a simulator. A life-sized terrain model was placed within a virtual reality environment, representing maritime environments, including port structures. To simulate ship motions according to maritime weather conditions, we applied various laws of physics within virtual reality. Finally, to provide validation data for critical navigation technologies, such as collision avoidance and ship detection, we generated a virtual automatic identification system and camera data. We implemented and operated a ship navigation simulator using this approach, and simulations conducted across various environments generated real-time sensor data efficiently, affirming the effectiveness of the proposed method.

STP4: spatio temporal path planning based on pedestrian trajectory prediction in dense crowds

This article proposes a means of autonomous mobile robot navigation in dense crowds based on predicting pedestrians’ future trajectories. The method includes a pedestrian trajectory prediction for a running mobile robot and spatiotemporal path planning for when the path crosses with pedestrians. The predicted trajectories are converted into a time series of cost maps, and the robot achieves smooth navigation without dodging to the right or left in crowds; the path planner does not require a long-term prediction. The results of an evaluation implementing this method in a real robot in a science museum show that the trajectory prediction works. Moreover, the proposed planning’s arrival times is 26.4% faster than conventional 2D path planning’s arrival time in a simulation of navigation in a crowd of 50 people.

Simulation of Sea Ice Fragmentation Based on an Improved Voronoi Diagram Algorithm in an Ice Zone Navigation Simulator

In order to reduce the cost of navigation training in the waters of ice zones and improve the effectiveness of the training process, a method for simulating sea ice fragmentation in an ice zone navigation simulator is proposed. The Voronoi diagram algorithm, which takes the ice thickness into account and affects the degree of fragmentation, was used to preprocess the sea ice model so that the number and sizes of the ice model fragmentations would be related to the ice thickness. According to the position of the preprocessed sub-blocks of the ice model, the collision bodies of the Mesh Collider and Sphere Collider were set up to realize the effect of the conduction of ice cracking as a result of the ship’s hull colliding with the ice surface. Based on the positional relationship between mesh triangle elements and the water surface, the volume of an ice floe that should have been underwater when it reached equilibrium was calculated to achieve the sea-floating effect of the broken ice floe. The quadtree method for the management of sea ice scenes was improved to improve the timeliness of the replacement of the ice model. The experiments show that this method improved the realism of simulations of sea ice breaking in ice zones and can be used for simulations in ice zone navigation simulators.

Simultaneous Localization and Mapping and Tag-Based Navigation for Unmanned Aerial Vehicles

This paper presents navigation techniques for an Unmanned Aerial Vehicle (UAV) in a virtual simulation of an indoor environment using Simultaneous Localization and Mapping (SLAM) and April Tag markers to reach a target destination. In many cases, UAVs can access locations that are inaccessible to people or regular vehicles in indoor environments, making them valuable for surveillance purposes. This study employs the Robot Operating System (ROS) to simulate SLAM techniques using LIDAR and GMapping packages for UAV navigation in two different environments. In the Tag-based simulation, the input topic for April Tag in ROS is camera images, and the calibration of position with a tag is done through assigning a message to each ID and its marker image. On the other hand, navigation in SLAM was achieved using a global and local planner algorithm. For localization, an Adaptive Monte-Carlo Localization (AMCL) technique has been used to identify factors contributing to inconsistent mapping results, such as heavy computational load, grid mapping accuracy, and inadequate UAV localization. Furthermore, this study analyzed the April Tag-based navigation algorithm, which showed satisfactory outcomes due to its lighter computing requirements. It can be ascertained that by using ROS packages, the simulation of SLAM and Tag-based UAV navigation inside a building can be achieved.

Modeling the influence of wind on ship circulation elements

When solving a number of practical problems of navigation and ship maneuvering, it is necessary to take into account the effect of wind on the parameters of the ship motion, including curvilinear motion, in particular, on circulation. There is very little information on this problem, especially in terms of quantitative estimates of the wind impact on circulation elements. Based on this, the purpose of this work is to study the effect of wind on the circulation elements based on mathematical modeling and to determine quantitative estimates of this effect when changing such factors as wind speed and heading angle, ship length and rudder angle. The simulation is carried out on a certified navigation simulator Transas NT Pro-5000. The mathematical model of vessel movement and wind effect used in this simulator is presented in the paper. A description of three simulated container ships with similar aerodynamic characteristics is given for the various heading angle and velocity of the wind before the start of the turn. In some experiments, the rudder angle is changed. The results of the simulation are presented in tabular and graphical forms. Quantitative estimates of the displacement of the turning points on the circulation by 90°, 180°, 270° and 360° at wind influence from the corresponding points of circulation in the absence of wind. The graphical dependences of these displacements on the heading angle of the wind and their analytical approximations are presented. The ranges of the wind heading angles at which the maximum effect of the wind on the circulation elements is observed are established. Quantitative estimates of the inversely proportional dependence of the circulation elements on the ship length are calculated. The hypotheses of the other authors about the direction of displacement of the circulation curve under wind action are tested. To verify the validity and reliability of the results obtained, it is necessary to perform similar studies using other mathematical models and natural experiments.

Marine Collision Avoidance Route Planning Model for MASS Based on Domain-Based Predicted Area of Danger

When the own ship encounters target ships in a close-quarter situation, an officer on watch needs to safely and timely alter the course of the vessel to avoid a collision. If ECDIS can automatically collect the navigation parameters and plot areas of collision as quasi-static obstruction areas, it will be much easier for seafarers to implement effective route planning. Hence, this study focuses on developing the MCARP model as a theoretical concept based on the DPAD model and LCD model. By operating the MCARP using ArcGIS, DPADs and several effective collision avoidance routes can be generated and imported into ECDIS based on AIS information at large scales and ample time. The graphic overlay of DPADs and effective routes on ECDIS can serve as a collision avoidance strategy reference for the personnel controlling maritime autonomous surface ships. Finally, different ships encountering situations were input into a Transas navigational simulator. The simulation results showed that own ship could avoid collisions with multiple target ships at distances larger than the preset collision avoidance distances, which also indicated that MCARP is practically feasible.