NeRF与3D高斯泼溅如何重塑SLAM：综述
How NeRFs and 3D Gaussian Splatting are Reshaping SLAM: a Survey
AI总结：
本文首次以辐射场（NeRF与3DGS）视角全面综述SLAM的演进，阐明背景、路径、优劣与挑战。
摘要：
在过去的二十年里，同时定位与地图构建（SLAM）领域的研究经历了重大演变，凸显了其在实现未知环境自主探索中的关键作用。这一演变从手工设计的方法开始，经过深度学习时代，发展到近期聚焦于神经辐射场（NeRFs）和3D高斯泼溅（3DGS）表示的研究。鉴于该领域研究日益增多且缺乏全面综述，本文旨在通过辐射场最新进展的视角，首次提供SLAM进展的全面概述。本文阐明了其背景、演进路径、固有优势与局限，并作为一份基础参考文献，以突出动态进展与具体挑战。
英文摘要：
Over the past two decades, research in the field of Simultaneous Localization and Mapping (SLAM) has undergone a significant evolution, highlighting its critical role in enabling autonomous exploration of unknown environments. This evolution ranges from hand-crafted methods, through the era of deep learning, to more recent developments focused on Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting (3DGS) representations. Recognizing the growing body of research and the absence of a comprehensive survey on the topic, this paper aims to provide the first comprehensive overview of SLAM progress through the lens of the latest advancements in radiance fields. It sheds light on the background, evolutionary path, inherent strengths and limitations, and serves as a fundamental reference to highlight the dynamic progress and specific challenges.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
