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How NeRFs and 3-D Gaussian Splatting Are Reshaping SLAM: A Survey

Fabio Tosi, Youmin Zhang, Ziren Gong, Erik Sandström, Stefano Mattoccia, Martin R. Oswald, Poggi Mg

2026IEEE Transactions on Robotics11 citationsDOI

Abstract

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 evo-lution 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) rep-resentations. 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.

Topics & Concepts

RadianceComputer scienceArtificial intelligenceComputer visionGaussianField (mathematics)Deep learningDeep neural networksSimultaneous localization and mappingGaussian processRobot visionMobile robotPotential fieldRobotArtificial neural networkRoboticsLight fieldLens (geology)Robotics and Sensor-Based LocalizationAdvanced Neural Network ApplicationsAdvanced Optical Sensing Technologies
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