Omniverse-OpenDS: Enabling Agile Developments for Complex Driving Scenarios via Reconfigurable Abstractions

Song, Zilin; Duan, Yicun; Jin, Wangkai; Huang, Shuchang; Wang, Shuolei; Peng, Xiangjun

doi:10.1007/978-3-031-04987-3_5

Cited by 8 publications

(1 citation statement)

References 22 publications

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“…Carla [7] is an open-source simulator that has been developed from the ground up to support the development, training, and validation of autonomous driving systems. A real-time cooperative design and simulation platform called Omniverse [8] was designed for Metaverses with the support of Nvidia's powerful graphic processing capabilities. Blender [9] is free open-source software that provides solutions for modeling, animation, rendering, and video creation.…”

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confidence: 99%

Parallel Sensing in Metaverses: Virtual-Real Interactive Smart Systems for “6S” Sensing

Shen¹,

Liu²,

Tian

et al. 2022

IEEE/CAA J. Autom. Sinica

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In the construction of Metaverses, sensors that are referred to as the "bridge of information transmission", play a key role. The functionality and efficiency of today's sensors, which operate in a manner similar to physical sensing, are frequently constrained by their hardware and software. In this research, we proposed the Parallel Sensing framework, which includes background, concept, basic methods and typical application of parallel sensing. In our formulation, sensors are redefined as the integration of real physical sensors and virtual software-defined sensors based on parallel intelligence, in order to boost the performance of the sensors. Each sensor will have a parallel counterpart in the virtual world within the framework of parallel sensing. Digital sensors serve as the brain of sensors and maintain the same properties as physical sensors. Parallel sensing allows physical sensors to operate in discrete time periods to conserve energy, while cloud-based descriptive, predictive, and prescriptive sensors operate continuously to offer compensation data and serve as guardians. To better illustrate parallel sensing concept, we show some example applications of parallel sensing such as parallel vision, parallel point cloud and parallel light fields, both of which are designed by construct virtual sensors to extend small real data to virtual big data and then boost the performance of perception models. Experimental results demonstrate the effective of parallel sensing framework. The interaction between the real and virtual worlds enables sensors to operate actively, allowing them to intelligently adapt to various scenarios and ultimately attain the goal of "Cognitive, Parallel, Crypto, Federated, Social and Ecologic" 6S sensing.

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confidence: 99%