20.8 Space-Mate: A 303.5mW Real-Time Sparse Mixture-of-Experts-Based NeRF-SLAM Processor for Mobile Spatial Computing

Recently, spatial computing has become popular in mobile devices, such as autonomous robots and augmented reality (AR) glasses [1], and it enables cyber-physical interaction through accurate user position and 3D geometric information of the surrounding environment obtained with the simultaneous loca...

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Bibliographic Details
Main Authors: Park, Gwangtae, Song, Seokchan, Sang, Haoyang, Im, Dongseok, Han, Donghyeon, Kim, Sangyeob, Lee, Hongseok, Yoo, Hoi-Jun
Format: Conference Proceeding
Language:English
Subjects:
Glass
Graphics processing units
Mobile handsets
Real-time systems
Simultaneous localization and mapping
Solid state circuits
Three-dimensional displays
Online Access:Request full text
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Summary:Recently, spatial computing has become popular in mobile devices, such as autonomous robots and augmented reality (AR) glasses [1], and it enables cyber-physical interaction through accurate user position and 3D geometric information of the surrounding environment obtained with the simultaneous localization and mapping (SLAM) algorithm. Previous SLAM processors [2-5] accelerated mapping and tracking, but they supported few (60MB) dense 3D map representation which stores color/distance values in high resolution (
ISSN:2376-8606
DOI:10.1109/ISSCC49657.2024.10454487