基于三维高斯基元场景表示的机器人稠密RGB-D SLAM算法

doi:10.13474/j.cnki.11-2246.2025.1115

测绘通报 ›› 2025, Vol. 0 ›› Issue (11): 99-103.doi: 10.13474/j.cnki.11-2246.2025.1115

基于三维高斯基元场景表示的机器人稠密RGB-D SLAM算法

张郭¹, 卫玲¹, 何胜喜^2,3

1. 重庆科创职业学院智能制造与机器人学院, 重庆 402160;
2. 重庆大学机械传动国家重点实验室, 重庆 400044;
3. 重庆长安汽车股份有限公司, 重庆 400023

收稿日期:2024-12-31 发布日期:2025-12-04
作者简介:张郭(1982—),男,副教授,高级实验师,主要研究方向为自动化控制技术等。E-mail:zg198207@163.com
基金资助:
国家自然科学基金(52005057)

Robot dense RGB-D SLAM algorithm based on 3D Gaussian primitive scene representation

ZHANG Guo¹, WEI Ling¹, HE Shengxi^2,3

1. Intelligent Manufacturing and Robotics College of Chongqing Science Techence Innovation Vocational College, Chongqing 402160, China;
2. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing 400044, China;
3. Chongqing Changan Automobile Co., Ltd., Chongqing 400023, China

Received:2024-12-31 Published:2025-12-04

摘要/Abstract

摘要： 稠密即时定位与地图构建(SLAM)是机器人中至关重要的技术。近期有关三维高斯溅射技术的研究表明,利用多个不同位姿的相机,可以实现高质量的场景重建与实时渲染。在此背景下,本文将三维高斯溅射技术引入SLAM,通过三维高斯基元对场景进行表征,利用RGB-D相机实现了稠密视觉SLAM算法。该算法克服了以往基于辐射场表示的局限性,特别是在快速渲染与优化、识别先前建图区域,以及通过添加更多高斯进行结构化地图扩展方面。大量试验结果表明,本文提出的稠密RGB-D SLAM算法在相机姿态估计、地图构建与新视图合成方面,比现有算法提高了最多2倍的性能。

关键词: SLAM, 三维高斯溅射, 定位, 建图, 机器人

Abstract: Dense simultaneous localization and mapping is a crucial technology in robotics.Recent research on 3D Gaussian splatting has demonstrated that high-quality scene reconstruction and real-time rendering can be achieved using multiple cameras in different poses.Against this backdrop,this paper introduces 3D Gaussian splatting into SLAM,representing the scene using 3D Gaussian primitives and implementing a dense visual SLAM algorithm using RGB-D cameras.This algorithm overcomes the limitations of previous radiance field-based representations,particularly in terms of fast rendering and optimization,the ability to recognize previously mapped regions,and structured map expansion by adding more Gaussians.Extensive experimental results demonstrate that the proposed dense RGB-D SLAM algorithm improves performance by up to 2 times compared to existing methods in terms of camera pose estimation,map construction,and new view synthesis.

Key words: SLAM, 3D Gaussian splatting, localization, mapping, robot

中图分类号:

P228

张郭, 卫玲, 何胜喜. 基于三维高斯基元场景表示的机器人稠密RGB-D SLAM算法[J]. 测绘通报, 2025, 0(11): 99-103.

ZHANG Guo, WEI Ling, HE Shengxi. Robot dense RGB-D SLAM algorithm based on 3D Gaussian primitive scene representation[J]. Bulletin of Surveying and Mapping, 2025, 0(11): 99-103.

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基于三维高斯基元场景表示的机器人稠密RGB-D SLAM算法

Robot dense RGB-D SLAM algorithm based on 3D Gaussian primitive scene representation

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