Science Data Visualization in AR/VR for Planetary and Earth Science
No abstract available
Grubb, Thomas G.↗
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University of Michigan AR/VR Final Presentation
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Amit Kothekar↗
Experience in Visualizing Satellite Data With AR/VR Technologies at NASA's GES-DISC
The Goddard Earth Sciences Data and Information Services Center (GES-DISC) at NASA plays a crucial role in archiving and disseminating vital Earth science data. In this project, we leverage immersive visualization technologies to reshape engagement with and comprehension of the intricate datasets of our planet. Through the adoption of immersive technologies, we are enhancing established methods, offering novel, intuitive experiences in visualizing and interacting with Earth science data. Our goal is to contribute to the ongoing evolution of data interaction, pushing the boundaries of what's possible in data interpretation and education.
Visualization↗
AR/VR CBRN Solution for Emergency Responders
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45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
FIRE: A Failure-Adaptive RL Framework for Edge Computing Migrations
In edge computing, users' service profiles are migrated between edge servers due to user mobility. Reinforcement Learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook occasional server failures, which although rare, impact latency-sensitive applications like AR/VR and real- time obstacle detection. These rare failures, being not adequately represented in historical training data, pose a challenge for data-driven RL algorithms. We introduce FIRE, a framework that adapts to rare events by training a RL policy in an edge computing digital twin environment. We propose FIRE-ImRE, an importance sampling-based Q-learning algorithm, which samples rare events proportionally to their impact on the value function. FIRE considers delay, migration, failure, and backup placement costs across individual and shared service profiles. We prove FIRE-ImRE's boundedness and convergence to optimality. Next, we introduce novel deep Q-learning (FIRE-ImDQL) and actor critic (FIRE-ImACRE) versions of our algorithm to enhance scalability. Here, we extend our framework to accommodate users with varying risk tolerances of rare failure events. Through trace-driven experiments, we show that FIRE reduces edge computing costs compared to vanilla RL and the greedy baseline in the event of failures.
Edge computing↗
exadigitUE5
This project provides the AR/VR interface to ORNL's exascale digital twin. The main functionality is implemented using Unreal Engine 5.1 for Desktop or Microsoft Hololens2 based visualization and interation with the system. The digital twin provides data ingestion from telemetry, as well as triggering and interacting with simulations developed for the wider ExaDigiT project at ORNL, as well as for the LUMI system at CSC and other CrayEX Supercomputers. For the overarching project, see ExaDigiT at https://exadigit.github.io, with the code repositories at https://code.ornl.gov/exadigit.
Maiterth, Matthias [Oak Ridge National Laboratory ↗
High Fidelity Aerospace Simulations at NASA Ames SimLabs
NASA Ames SimLabs is home to unique simulation facilities capable of a wide range of aerospace systems research. This presentation will focus on the Vertical Motion Simulator with thoughts on future AR/VR applications and research.
simulation↗
High Fidelity Aerospace Simulations at NASA Ames SimLabs
An overview of the simulation facilities at SimLabs at NASA Ames. Main focus is on the Vertical Motion Simulator or VMS, also brief descriptions of other simulators. Discussion of the history and general specifications of the VMS. Also, provide an overview of past research and training conducted on the simulators, and some future developments with a focus on AR/VR technologies.
flight simulators↗
Human Research Program: Human Factors and Behavioral Performance
This discussion provides an overview of the Human Research Program (HRP), the Human Factors and Behavioral Performance Element (HFBP), and outlines currently documented research using AR/VR or Hybrid Reality to maintain or improve human behavior for long duration exploration mission environments. Different analog environments are also discussed in this presentation (ISS and HERA).
Human Research Program↗
Rapid Model Import Tool (RMIT) User Guide
The NASA Rapid Model Import Tool (RMIT) is designed to import 3D models built in commercially available Computer Aided Design (CAD) and Digital Content Creation (DCC) development software such as; Catia, Creo, 3DS Max, Maya, etc. Upon import, RMIT processes the models to reduce file size and exports the results in a format compatible with Augmented Reality (AR) and Virtual Reality (VR) development software applications. RMIT intends to make CAD models directly accessible to engineers from local AR/VR compatible laptops and desktops.
Joseluis Chavez↗
Human Research Program: Human Factors and Behavioral Performance Research to Enable Artemis
This discussion provides an overview of the human research program (HRP), the Human Factors and Behavioral Performance Element (HFBP), and outlines currently documented research using AR/VR or Hybrid Reality to maintain or improve human behavior for long duration exploration mission environments. Different analog environments are also discussed in this presentation (ISS and HERA).
Human Research Program↗
The Future of Visualization Technology Vis in Practice
Two decades ago, we witnessed an inflection point as graphics programming became commoditized. A comparable inflection point may be on the horizon, this time driven by the commoditization of immersive display technology with Augmented Reality (AR), Virtual Reality (VR), and Extended Reality (XR) technologies poised to redefine our interaction with data, environments, and collaboration. To drive the technology and its application, we should consider the lessons learned from successful large-scale immersive installations. Where these installations have thrived is by enhancing traditional workflows rather than entirely replacing them, supporting improved judgments of complex spaces, direct interaction in 3D, and embedding high-dimensional data.
AR/VR↗