Unreal Engine Research Articles

Framework for real-time computation and streaming of soundscapes

The auralization of dynamic soundscapes brings significant computational challenges, as multiple often moving sources have to be considered simultaneously. Making such auralizations interactive rules out pre-rendering, requiring the underlying computations to be performed in real-time instead. The “Virtual Acoustics” (VA) framework allows for such real-time applications by leveraging geometrical acoustics and efficient multi-threading. Delivering these simulations to a larger audience, however, has proven difficult, as they still require a lengthy setup and possible simulation complexity is highly dependent on available hardware. When also including high-fidelity 3D visualization, hardware requirements rise further, hindering remote deployment. We present a web-based approach that executes simulations on a server and streams the result in real-time, offloading heavy calculations to a sufficiently powerful machine. 3D graphics are rendered by Unreal Engine and streamed using Pixel Streaming. VA auralization is transmitted via WebRTC audio streams. Both visualization and auralization are ultimately aggregated in a single website for platform-independent access. User input is gathered by the website and relaid back to the server, making the experience interactive. Thereby, this approach can deliver high-fidelity virtual environments with minimal setup and hardware requirements for the user. The approach will be demonstrated by streaming an interactive city park soundscape.

Pre-Dam Vltava River Valley—A Case Study of 3D Visualization of Large-Scale GIS Datasets in Unreal Engine

This article explores the potential of the Unreal Engine as a tool for creating realistic 3D visualizations of large-scale areas (1000 km2 and more) using GIS datasets. Unlike small-scale visualizations, large-scale visualizations are rare and often not public, which presents significant problems since they present different challenges and require different approaches. This article presents several relevant scientific studies and projects that have successfully used game engines for similar purposes. This case study focuses on the computational techniques used in Unreal Engine for the 3D visualization of GIS data and the potential application of Unreal Engine in large-scale geo-visualizations. It explores the potential for using GIS data within a game engine, including plug-ins that provide additional functionality for working with GIS data, such as the Vitruvio plug-in to implement procedural modeling of buildings. The case study is applied to GIS datasets of the historical Vltava Valley covering an area of 1670 km2 to demonstrate the unique challenges of using Unreal Engine to create realistic visualizations of large-scale historical landscapes. The resulting visualizations are presented. The practical application of this research provides insights into the potential of the Unreal Engine as a tool for creating realistic 3D visualizations of large-scale historical areas.

Executing realistic earthquake simulations in unreal engine with material calibration

Earthquakes significantly impact societies and economies, underscoring the need for effective search and rescue strategies. As AI and robotics increasingly support these efforts, the demand for high-fidelity, real-time simulation environments for training has become pressing. Earthquake simulation can be considered as a complex system. Traditional simulation methods, which primarily focus on computing intricate factors for single buildings or simplified architectural agglomerations, often fall short in providing realistic visuals and real-time structural damage assessments for urban environments. To address this deficiency, we introduce a real-time, high visual fidelity earthquake simulation platform based on the Chaos Physics System in Unreal Engine, specifically designed to simulate the damage to urban buildings. Initially, we use a genetic algorithm to calibrate material simulation parameters from Ansys into the Unreal Engine’s fracture system, based on real-world test standards. This alignment ensures the similarity of results between the two systems while achieving real-time capabilities. Additionally, by integrating real earthquake waveform data, we improve the simulation’s authenticity, ensuring it accurately reflects historical events. All functionalities are integrated into a visual user interface, enabling zero-code operation, which facilitates testing and further development by cross-disciplinary users. We verify the platform’s effectiveness through three AI-based tasks: similarity detection, path planning, and image segmentation. This paper builds upon the preliminary earthquake simulation study we presented at IMET 2023, with significant enhancements, including improvements to the material calibration workflow and the method for binding building foundations.

Assessing Ambisonics Sound Source Localization by Means of Virtual Reality and Gamification Tools

Sound localization is a key area of interest in auditory research, especially in complex acoustic environments. This study evaluates the impact of incorporating higher-order Ambisonics (HOA) with virtual reality (VR) and gamification tools on sound source localization. The research addresses the current limitations in VR audio systems, particularly the lack of native support for HOA in game engines like Unreal Engine (UE). A novel framework was developed, combining UE for VR graphics rendering and Max for HOA audio processing. Participants performed sound source localization tasks in two VR environments using a head-mounted display (HMD). The assessment included both horizontal and vertical plane localization. Gamification elements were introduced to improve engagement and task comprehension. Results showed significant improvements in horizontal localization accuracy, although challenges remained in back localization. The findings underscore the potential of VR and gamification to enhance auditory tests, reducing test duration and participant fatigue. This research contributes to the development of immersive and interactive audio experiences, highlighting the broader applications of VR beyond entertainment.

A Novel Dynamically Adjusted Entropy Algorithm for Collision Avoidance in Autonomous Ships Based on Deep Reinforcement Learning

Decision-making for collision avoidance in complex maritime environments is a critical technology in the field of autonomous ship navigation. However, existing collision avoidance decision algorithms still suffer from unstable strategy exploration and poor compliance with regulations. To address these issues, this paper proposes a novel autonomous ship collision avoidance algorithm, the dynamically adjusted entropy proximal policy optimization (DAE-PPO). Firstly, a reward system suitable for complex maritime encounter scenarios is established, integrating the International Regulations for Preventing Collisions at Sea (COLREGs) with collision risk assessment. Secondly, the exploration mechanism is optimized using a quadratically decreasing entropy method to effectively avoid local optima and enhance strategic performance. Finally, a simulation testing environment based on Unreal Engine 5 (UE5) was developed to conduct experiments and validate the proposed algorithm. Experimental results demonstrate that the DAE-PPO algorithm exhibits significant improvements in efficiency, success rate, and stability in collision avoidance tests. Specifically, it shows a 45% improvement in success rate per hundred collision avoidance attempts compared to the classic PPO algorithm and a reduction of 0.35 in the maximum collision risk (CR) value during individual collision avoidance tasks.

Deformable patch-based garment design in immersive virtual reality

PurposeThis study aims to create and deform 3D garment apparel in an immersive virtual reality using head-mounted display and controllers. For this, adequate design methods for immersive virtual environment were explored and developed in order to confirm the suitability of the developed methods.Design/methodology/approachAn immersive virtual environment was prepared using Unreal Engine (UE) version 5.1 and Meta Human Lexi to create template garment that corresponds to the sizes of a human model. Dual quaternion skinning was adopted for pose deformation. For size deformation, patches were constructed with the measurement lines defined on Lexi. This patch-based approach was adopted not only for automatic generation but also for flat pattern projection of the template garment.FindingsThe research found that garment-making process can be brought into immersive virtual reality. Free use of one's hands and body made apparel deformation in an immersive environment conform with the real garment draping process.Originality/valueSimulating garment making in an immersive virtual reality has not previously been explored in detail. This research discovered, implemented and tested methods that best suit the environment where head-mounted display and controllers are essential in detail.

Research on assembly constraints reconstruction based on Unreal Engine

Abstract In the process of digital twin modeling, the assembly constraints of the model in the Unreal Engine usually requires manual intervention. To realize the intelligence and high efficiency of digital twin modeling, an Unreal Engine based assembly constraints reconstruction method is proposed. The method explores the high-fidelity assembly constraints mapping from the modeling software to the Unreal Engine, divides the model in the modeling software into two parts: the entity structure and the assembly constraints, and reconstructs the assembly constraints in the Unreal Engine, to realize the transformation from the modeling software model to the Unreal Engine model. Finally, the proposed method is applied to the digital twin engineering of various institutions to verify its rapidity and effectiveness in practical application scenarios.

Advanced techniques and high-performance computing optimization for real-time rendering

Real-time rendering is a cornerstone of modern interactive media, enabling the creation of immersive and dynamic visual experiences. This paper explores advanced techniques and high-performance computing (HPC) optimization in real-time rendering, focusing on the use of game engines like Unity and Unreal Engine. It delves into mathematical models and algorithms that enhance rendering performance and visual quality, including Level of Detail (LOD) management, occlusion culling, and shader optimization. The study also examines the impact of GPU acceleration, parallel processing, and compute shaders on rendering efficiency. Furthermore, the paper discusses the integration of ray tracing, global illumination, and temporal rendering techniques, and addresses the challenges of balancing quality and performance, particularly in virtual and augmented reality applications. The future role of artificial intelligence and machine learning in optimizing real-time rendering pipelines is also considered. By providing a comprehensive overview of current methodologies and identifying key areas for future research, this paper aims to contribute to the ongoing advancement of real-time rendering technologies.

Exploring the Frontiers of Space in 3D

An immersive, virtual exhibit of large telescopes and space missions is described. The exhibit overcomes the difficulty members of the public have in appreciating the scale and complexity of modern, astronomical research facilities. Using very detailed 3D models, ground- and space-based telescopes that are impossible to visit in person can be explored through a virtual space, created with Epic Games’ Unreal Engine tool.

Using Real-Time Ray Tracing in Game Action-Adventure ANGKARA "The Rise of Asura"

The pressing problems facing the games industry in Indonesia are first, the lack of developers who can meet the needs of the local market and the lack of adaptation of local content in games. Second, how to improve the optimization of the Ray Tracing process? To overcome these challenges, this research aims to design and build an action-adventure game model using Unreal Engine 5. By developing the Real-Time Ray Tracing (RTRT) feature. The game design will also utilize the latest technology such as Ray Tracing, and artificial intelligence to create an immersive and realistic gaming experience. The method used in this research is GDLC (Game Development Life Cycle). The results of research using black box testing with components, character responsiveness, basic attacks, interaction with the environment, defense, enemy behavior, and optimization of Ray Tracing state that it has been validated.

Application of Deep Reinforcement Learning to Defense and Intrusion Strategies Using Unmanned Aerial Vehicles in a Versus Game

Drones are used in complex scenes in different scenarios. Efficient and effective algorithms are required for drones to track targets of interest and protect allied targets in a versus game. This study used physical models of quadcopters and scene engines to investigate the resulting performance of attacker drones and defensive drones based on deep reinforcement learning. The deep reinforcement learning network soft actor-critic was applied in association with the proposed reward and penalty functions according to the design scenario. AirSim UAV physical modeling and mission scenarios based on Unreal Engine were used to simultaneously train attacking and defending gaming skills for both drones, such that the required combat strategies and flight skills could be improved through a series of competition episodes. After 500 episodes of practice experience, both drones could accelerate, detour, and evade to achieve reasonably good performance with a roughly tie situation. Validation scenarios also demonstrated that the attacker–defender winning ratio also improved from 1:2 to 1.2:1, which is reasonable for drones with equal flight capabilities. Although this showed that the attacker may have an advantage in inexperienced scenarios, it revealed that the strategies generated by deep reinforcement learning networks are robust and feasible.

Game Engines for Immersive Visualization: Using Unreal Engine Beyond Entertainment

Abstract One core aspect of immersive visualization labs is to develop and provide powerful tools and applications that allow for efficient analysis and exploration of scientific data. As the requirements for such applications are often diverse and complex, the same applies to the development process. This has led to a myriad of different tools, frameworks, and approaches that grew and developed over time. The steady advance of commercial off-the-shelf game engines such as Unreal Engine has made them a valuable option for development in immersive visualization labs. In this work, we share our experience of migrating to Unreal Engine as a primary developing environment for immersive visualization applications. We share our considerations on requirements, present use cases developed in our lab to communicate advantages and challenges experienced, discuss implications on our research and development environments, and aim to provide guidance for others within our community facing similar challenges.

Joining SUMO and Unreal Engine to Create a Bespoke 360 Degree Narrow Passage Driving Simulator

The use of simulators is widespread in driver behavioural research. The ability of driving simulators to achieve the high levels of behavioural fidelity desired by behavioural researchers is argued to be resultant of the physical fidelity of the simulator. Whilst attempts to maximise the physical fidelity of simulators have often been focused on the hardware capabilities of the simulator, the software of the simulator has been argued to be as important. This is because the software of a simulator controls the intelligence and the heterogeneity of the behaviours of the simulated vehicles, as well as the quality of the graphics of the simulation. Despite the importance of intelligent simulated agents, previous driving simulator studies have tended to simplify the behaviours of simulated vehicles and the scenarios that are presented to participants. This is particularly true of simulator studies investigating the decision-making of drivers at narrow passages, a relatively unregulated but hazardous situation in which two opposing vehicles must negotiate how to safely pass through a road narrowing, in which the interactive nature of the interaction has often been neglected. Following a review of the requirements for a representative narrow passage driving simulator, it is argued that co-simulation, an approach which combines multiple simulator types to create a global simulation, provides the best approach to creating intelligent simulated agents within an immersive environment for narrow passage behavioural research. As such, the development of a simulator for narrow passage behavioural research that combines SUMO and Unreal Engine is described. In particular, the development of a novel narrow passage behavioural model within SUMO that utilises previous behavioural findings is highlighted. To this end, it is argued that this approach facilitates higher levels of behavioural fidelity for narrow passage interaction studies and provides a framework for the investigation of other driver behaviours.

The application and algorithm of fabric simulation in game industry

fabric simulation has emerged as a crucial aspect of computer graphics, particularly in applications such as film production, video games, and design. This paper provides a comprehensive review of fabric simulation methodologies, implementation techniques, and its diverse applications within the game industry. The fabric simulation algorithms are broken down into Fabric Modeling, Dynamic Simulation, and Collision Handling. The three common modeling strategies of Elasticity-Based Models, Particle-Based Models, and Mass-Spring Damper Models, are discussed in detail. Additionally, dynamic simulation strategies such as Position-Based Dynamics (PBD) and Extended Position-Based Dynamics (XPBD) are explored for their role in real-time simulations, particularly in the game industry. The paper also delves into collision handling algorithms, exploring the strategies for accurate collision detection and response. The application of fabric simulation in the game industry is highlighted, showcasing how it enhances realism and immersion by simulating fabric movement and interactions with the environment. The paper introduced various fabric simulation tools and systems within popular game engines like Unity 3D and Unreal Engine 5. Furthermore, optimization strategies, such as view-dependent adaptive simulation, are discussed to improve performance providing insight for future work.

The application and algorithm of fabric simulation in game industry

fabric simulation has emerged as a crucial aspect of computer graphics, particularly in applications such as film production, video games, and design. This paper provides a comprehensive review of fabric simulation methodologies, implementation techniques, and its diverse applications within the game industry. The fabric simulation algorithms are broken down into Fabric Modeling, Dynamic Simulation, and Collision Handling. The three common modeling strategies of Elasticity-Based Models, Particle-Based Models, and Mass-Spring Damper Models, are discussed in detail. Additionally, dynamic simulation strategies such as Position-Based Dynamics (PBD) and Extended Position-Based Dynamics (XPBD) are explored for their role in real-time simulations, particularly in the game industry. The paper also delves into collision handling algorithms, exploring the strategies for accurate collision detection and response. The application of fabric simulation in the game industry is highlighted, showcasing how it enhances realism and immersion by simulating fabric movement and interactions with the environment. The paper introduced various fabric simulation tools and systems within popular game engines like Unity 3D and Unreal Engine 5. Furthermore, optimization strategies, such as view-dependent adaptive simulation, are discussed to improve performance providing insight for future work.

Detection and Assessment of Seismic Response of High-Speed Railway Bridges Based on Smartphone Public Participation

The seismic response detection and operational safety assessment of high-speed railway (HSR) bridges play a crucial role in ensuring HSR systems’ operational safety and reliability. Smartphones have introduced intelligent inspection tools for structural health detection, becoming a new tool for intelligent structural inspection. Combining the public and smartphones is the key to public participation in structural health detection. This study utilizes smartphone-based structural seismic response inspection technology to investigate the framework of public participation in earthquake response inspection and assessment. This system comprises the Smart Bridge Brain (SBB), which integrates data from multiple sources and systems, an assigning mechanism for public participation inspection tasks, and smartphone-based HSR bridge structural seismic response inspection technology. At the same time, the Unreal Engine 5.0 software is used to create a mixed-reality virtual simulation experimental environment to validate the feasibility of this framework. The results indicate that the intelligent optimization of task allocation by the SBB successfully assigns detection tasks to each public participant. Public participants can promptly reach predefined damage structure detection targets and rapidly inspect bridge structural seismic response indicators using smartphones. In addition, this paper also conducts a comprehensive evaluation and analysis of the detection of the work efficiency index (WEI) within the system. Furthermore, optimization strategies for the efficient execution of detection tasks are proposed based on WEI variations influenced by different factors. The system framework is expected to enhance cluster-based HSR bridges’ intelligent disaster prevention and mitigation capabilities.

Empirical insights into AI-assisted game development: A case study on the integration of generative AI tools in creative pipelines

<p>This study conducts an empirical exploration of generative Artificial Intelligence (AI) tools across the game development pipeline, from concept art creation to 3D model integration in a game engine. Employing AI generators like Leonardo AI, Scenario AI, Alpha 3D, and Luma AI, the research investigates their application in generating game assets. The process, documented in a diary-like format, ranges from producing concept art using fantasy game prompts to optimizing 3D models in Blender and applying them in Unreal Engine 5. The findings highlight the potential of AI to enhance the conceptualization phase and identify challenges in producing optimized, high-quality 3D models suitable for game development. This study reveals the current limitations and ethical considerations of AI in game design, suggesting that while generative AI tools hold significant promise for transforming game development, their full integration depends on overcoming these hurdles and gaining broader industry acceptance.<strong></strong></p>

Data Management Framework for Highways: An Unreal Engine-Based Digital Sandbox Platform

The problems of information isolation, inefficiency, and paper-based data archiving in traditional highway survey and design methods are investigated in this paper. A novel digital sandbox platform framework was developed to promote the efficiency of route design, model data integration, and information sharing. Under the presented framework, an integrated application method for both the Building Information Modeling (BIM) and Geographic Information System (GIS) technologies was designed by using Unreal Engine technology. Firstly, a digital base model was established by integrating multi-disciplinary BIM model data and GIS three-dimensional (3D) multi-scale scene model data. On this basis, using Unreal Engine technology for visualization development, a digital sandbox platform with the data visualization, traffic organization simulation analysis, 3D spatial analysis, component information query, and scene switching functions was developed, which satisfies the 3D visualization and digitalization needs in the current highway planning and design. Additionally, the Analytic Hierarchy Process (AHP) was employed to analyze the impact of digital base model on the development and application of platform modules, including five crucial factors: data accuracy, data representation, multi-source data fusion, data management capability, and scene semantic representation. Finally, the research results indicate that the proposed digital sandbox platform framework provides users with a platform for integrated data management, information sharing, and 3D data visualization, while reducing design time by 30%, total design cost by 12%, and land occupancy rate by 10%.

Reverberation divergence in VR applications

This project aimed to investigate the correlation between virtual reality (VR) imagery and ambisonic sound. With the increasing popularity of VR applications, understanding how sound is perceived in virtual environments is crucial for enhancing the immersiveness of the experience. In the experiment, participants were immersed in a virtual environment that replicated a concert hall. Their task was to assess the correspondence between sound scenes (which differed in reverberation times and their characteristics) and the observed invariant visual scene. The research was conducted using paired tests. Participants were asked to identify the sound scene they considered more closely matched the concert hall seen in the VR goggles for each pair. Each sound scene differed in the employed impulse response. All the impulse responses were recorded in real venues such as concert halls, auditoriums, churches, etc. To provide a realistic auditory experience, the sound scenes were processed using third-order ambisonics and decoded using binaural techniques with HRTFs. The virtual concert hall was generated using the Unreal Engine and was the same for all the tests. One of the major conclusions drawn from the conducted research was confirming the role of spatial sound in creating immersive VR experiences. The study demonstrated that appropriately matching spatial sound to the VR visual scene is essential for achieving complete immersion. Additionally, expectations and preferences regarding reverberation characteristics in different types of spaces were discovered. These findings have significant implications for the design of virtual environments, and understanding these aspects can contribute to improving VR technology and creating more immersive and realistic virtual experiences for users.

Перспектива развития VR-технологий в образовании и социальной жизни

VR-based technologies are in demand in modern education. They create virtual environment and simulate processes similar to real ones. As a result, students can practice actions that form and consolidate the necessary competencies. This article describes the possibilities of using virtual reality to teach food-industry university students to design production sites, e.g., an independent virtual simulation where students could work on their own projects and developments. The proposed technology offers an improved import-substituting software that creates realistic models of food production, e.g., virtual food processing workshops where students could test and improve their skills in dealing with key parameters and technological processes. The program recreates technological solutions in virtual reality, which simplifies, speeds up, and reduces the cost of developing skills in production site design. This application is the most promising direction for VR technology in education. The software product was developed in the VR laboratory of Kemerovo State University. It allows students to design industrial buildings of various sizes, workshops, and production facilities of various capacities, as well as public catering places and their interior, open public spaces, e.g., city parks, etc. The product has a database for storing and using education materials, design blanks, and ready-made 3D models of equipment created in Unreal Engine. The 3D model database contains digital models of real-life devices and equipment used at food industry enterprises. The projects can be displayed in a visual digital environment to study the principles of equipment operation, monitor and change their parameters, and simulate faults and deviations. The database makes it possible to design small enterprises and large industrial complexes for food production in virtual environment.