Back to Search Start Over

A systemic survey of the Omniverse platform and its applications in data generation, simulation and metaverse

Authors :
Naveed Ahmed
Imad Afyouni
Hamzah Dabool
Zaher Al Aghbari
Source :
Frontiers in Computer Science, Vol 6 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

Nvidia’s Omniverse platform represents a paradigm shift in the realm of virtual environments and simulation technologies. This paper presents a comprehensive examination of the Omniverse platform, a transformative force in virtual environments and simulation technologies. We offer a detailed systematic survey of the Omniverse’s impact across various scientific fields, underscoring its role in fostering innovation and sculpting the technological future. Our focus includes the Omniverse Replicator for generating synthetic data to address data insufficiency, and the utilization of Isaac Sim with its Issac Gym and software development kit (SDK) for robotic simulations, alongside Drive Sim for autonomous vehicle emulation. We further investigate the Extended Reality (XR) suite for augmented and virtual realities, as well as the Audio2Face application, which translates audio inputs into animated facial expressions. A critical analysis of Omniverse’s technical architecture, user-accessible applications, and extensions are provided. We contrast existing surveys on the Omniverse with those on the metaverse, delineating their focus, applications, features, and constraints. The paper identifies potential domains where the Omniverse excels and explores its real-world application capabilities by discussing how existing research papers utilize the Omniverse platform. Finally, we discuss the challenges and hurdles facing the Omniverse’s broader adoption and implementation, mitigating the lack of surveys solely focusing on the Omniverse.

Details

Language :
English
ISSN :
26249898
Volume :
6
Database :
Directory of Open Access Journals
Journal :
Frontiers in Computer Science
Publication Type :
Academic Journal
Accession number :
edsdoj.59fdc5057a1e49398c85e69b69a0b11f
Document Type :
article
Full Text :
https://doi.org/10.3389/fcomp.2024.1423129