English(EN) Localization and Neural Splatting on the Edge: An FPGA Scene Memory for Robots

基于FPGA的LENS系统为边缘机器人带来GPU级场景内存

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-26 04:00

研究人员开发了LENS系统，旨在使资源受限的机器人能够在不依赖高功耗台式GPU的情况下执行场景内存任务。该系统利用FPGA和ARM平台加速场景坐标回归（SCR）和3D高斯泼溅（3DGS）渲染，实现了具有竞争力的定位精度和新视角合成质量。与NVIDIA Jetson Orin NX相比，LENS在每瓦性能和低延迟方面表现更优，尽管设备端训练仍落后于GPU能力。 AI

影响使边缘设备上的AI能力更强，减少对云处理复杂视觉任务的依赖。

排序理由该条目描述了一个新系统和一篇详细介绍其在特定硬件上性能的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Haohua Que, Mingkai Liu, Tianle Zhu, Handong Yao · 2026-10-26 04:00

边缘端的本地化与神经辐射场：面向机器人的FPGA场景内存

arXiv:2610.25068v2 Announce Type: replace-cross Abstract: Resource-constrained robots and autonomous vehicles need scene memories that localize a camera and render nearby views without a desktop GPU. Scene-coordinate regression (SCR) and 3D Gaussian splatting (3DGS) fit because t…

本文如何被排名

报道来源 [1]

边缘端的本地化与神经辐射场：面向机器人的FPGA场景内存

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