Featured Projects

VR Training on Issues of Youth Firearm Possession

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 Virtual Reality Training on Issues of Youth Firearm Possession.

PI. Tang. 8/5/2024-8/4/2025. $20,000. 

Funded by the God.Restoring.Order (GRO) Community, this research project will develop several VR scenarios that simulate environments designed to educate youth on applying critical skills in risky situations.

Team: Ming Tang, XR-Lab, Aaron Mallory, GRO.

XR-Lab students: Aayush Kumar, Mario Bermejo, Jonny Peng, Ahmad Alrefai, Rohit Ramesh, Charlotte Bodie 

The XR-Lab collaborated with the GRO community to leverage advanced extended reality (XR) technologies in the development of a virtual reality (VR) training application designed to strengthen the curriculum by reinforcing key competencies through immersive learning activities. In partnership, we evaluated the feasibility of integrating VR technology into the GRO training program, providing participants with an engaging narrative framework while equipping them with practical knowledge applicable to real-world contexts. The immersive VR scenarios addressed high-risk situations, including firearm possession and substance use, thereby creating a controlled environment for experiential learning and skill development.

The XR-Lab has harnessed advanced motion capture technology in this project to translate the movements of real people into lifelike digital characters. Every gesture, shift in posture, and subtle facial expression is carefully recorded and mapped to ensure authenticity and emotional depth in the virtual environment.

Our development team has worked closely and continuously with the GRO community, engaging in multiple motion studies, rehearsals, and testing sessions. This collaboration allows us to capture not just movement, but the nuance behind each action — the personality conveyed through body language, and the emotional context embedded in facial expression.

Through this process, the digital characters become more than avatars; they become authentic extensions of human experience, reflecting the stories. The result is an immersive, emotionally resonant experience where technology and humanity move together. 

 

GenAI+AR Siemens

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Automatic Scene Creation for Augmented Reality Work Instructions Using Generative AI. Siemens. PI. Ming Tang. co-PI: Tianyu Jiang. $25,000. UC. 4/1/2024-12/31/2024

Students: Aayush Kumar, Mikhail Nikolaenko, Dylan Hutson.

Sponsor: Siemens through UC MME Industry 4.0/5.0 Institute

Investigate integration of LLM Gen-AI with Hololens-based training. 

Reinforcement Learning

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XR-Lab’s project was selected to join the  Undergraduates Pursuing Research in Science and Engineering (UPRISE) Program
UNDERGRADUATE SUMMER RESEARCH PROGRAM IN SCIENCE AND ENGINEERING
May 6 – July 26, 2024

 

Project title: Reinforcement Learning (RL) system in Game Engine

Student: Mikhail Nikolaenko. UC. PI: Ming Tang. 

This project proposes the development of a sophisticated reinforcement learning (RL) system utilizing the robust and versatile environment of Unreal Engine 5 (UE5). The primary objective is to create a flexible and highly realistic simulation platform that can model a multitude of real-life scenarios, ranging from object recognition, urban navigation to emergency response strategies. This platform aims to significantly advance the capabilities of RL algorithms by exposing them to complex, diverse, and dynamically changing environments. Leveraging the advanced graphical and physical simulation capabilities of UE5, the project will focus on creating detailed and varied scenarios in which RL algorithms can be trained and tested. These scenarios will include, but not be limited to, urban traffic systems, natural disaster simulations, and public safety response models. The realism and intricacy of UE5’s environment will provide a challenging and rich training ground for RL models, allowing them to learn and adapt to unpredictable variables akin to those in the real world.

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P&G Metaverse

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Title: Leveraging Metaverse Platforms for Enhanced Global Professional Networking – Phase 1

Ming Tang, Principal Investigator

Amount: $32,416

Funding: P&G Digital Accelerator.

Gotal: Metaverse technologies for global engagement. Human-Computer Interaction, Digital Human. Immersive visualization. 

  • P&G Team. : Elsie Urdaneta, Sam Azeba. Paula Saldarriaga, JinnyLe HongOanh
  • UC Team: Ming Tang, Students: Nathaniel Brunner, Ahmad Alrefai, Sid Urankar

In Phase 1 of the “Leveraging Metaverse Platforms for Enhanced Global Professional Networking” project, conducted in partnership with P&G, the XR-Lab proposes a pilot study aimed at identifying and analyzing the top five metaverse platforms best suited for professional networking and conferencing.  The metaverse has opened unprecedented opportunities for communication, collaboration, and social engagement, offering innovative solutions for professional networking and conferencing. In Phase 1, “Surveying the Current Metaverse Landscape,” the UC team examined the top five metaverse platforms to evaluate their potential for replicating global in-person professional networking experiences and supporting multi-user online conferences.

This phase provided a systematic assessment of the leading platforms suitable for professional networking and conferencing. The team analyzed how these platforms leverage emerging technologies to create immersive experiences, such as hosting online conferences and facilitating discussions with global experts. The Phase 1 final report delivered a comprehensive evaluation of the strengths and limitations of each platform, along with recommendations for platform selection based on specific criteria such as audience size, interactivity, and technical requirements.

Additionally, the UC team demonstrated how platforms such as Mesh and Hyperspace can be customized for specific events, including tailored branding and interactive features designed to enhance professional networking and conferencing. These demonstrations provide valuable insights for P&G, highlighting how metaverse technologies can be strategically developed and adopted to expand global engagement and enable innovative event experiences.

Customized Metaverse Demo developed by the UC Team.

Please reach out to the P&G Team for the final report. 

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Digital Twin, LLM & IIOT

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IIOT for legacy and intelligent factory machines with XR and LLM feedback with a Digital Twin demonstration of real-time IOT for architecture/building applications using Omniverse. 

  • PIs: Sam Anand, Ming Tang.
  • Students: Anuj Gautama, Mikhail Nikolaenko, Ahmad Alrefai, Aayush Kumar, Manish Raj Aryal,c, Eian Bennett, Sourabh Deshpande 

$40,000. UC Industry 4.0/5.0 Institute Consortium Research Project: 01.2024-01.2025

The project centers on the development of a Digital Twin (DT) and a multi-agent Large Language Model (LLM) framework designed to access and interpret real-time and historical data through an Industrial Internet of Things (IIoT) platform. Real-time data is sourced from legacy machines and smart machines, integrating Building Information Modeling (BIM) with environmental sensors. The multi-agent LLM framework comprises specialized agents and supports diverse user interfaces, including screen-based systems, Virtual Reality (VR) environments, and mobile devices, enabling versatile interaction, data visualization, and analysis.

The research evaluates leading DT platforms—Autodesk Tandem, NVIDIA Omniverse, and Unreal Engine—focusing on their capabilities to integrate IoT and BIM data while supporting legacy machine systems.  Autodesk Tandem excelled in seamlessly combining BIM metadata with real-time IoT streams for building operations and system scalability.  NVIDIA Omniverse demonstrated unmatched rendering fidelity and collaborative features through its Universal Scene Description (USD) framework. Unreal Engine, notable for its immersive visualization, proved superior for LLM integration, leveraging 3D avatars and conversational AI to enhance user interaction.

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