激光测距传感器在三维重建中的技术研究
摘 要
随着三维重建技术在工业检测、虚拟现实、智能机器人等领域的广泛应用，对高精度、高效能的三维数据获取手段需求日益迫切。激光测距传感器凭借其测量精度高、抗干扰能力强等优势成为三维重建的重要工具，本研究旨在深入探讨激光测距传感器在三维重建中的应用技术。通过分析不同场景下激光测距传感器的工作原理与特性，提出了一种基于多源激光测距数据融合的三维重建算法，该算法结合了三角法和飞行时间法两种测距方式的优点，有效提高了重建精度与效率。实验结果表明，所提出的算法在复杂环境下仍能保持较高的重建质量，重建误差控制在毫米级别以内，相较于传统单一测距方法，重建速度提升了约30%。此外，针对激光测距传感器存在的数据缺失问题，引入深度学习算法进行数据修复，进一步完善了重建模型。本研究不仅为激光测距传感器在三维重建中的应用提供了新的思路和技术支持，而且对于推动三维重建技术向更高精度、更广范围发展具有重要意义。
关键词：激光测距传感器 三维重建 多源数据融合
Abstract
With the widespread application of 3D reconstruction technology in fields such as industrial inspection, virtual reality, and intelligent robotics, there is an increasing demand for high-precision and high-efficiency methods of acquiring 3D data. Laser rangefinder sensors have become essential tools for 3D reconstruction due to their advantages of high measurement accuracy and strong anti-interference capability. This study aims to explore the application technologies of laser rangefinder sensors in 3D reconstruction. By analyzing the working principles and characteristics of laser rangefinder sensors under different scenarios, a 3D reconstruction algorithm based on multi-source laser ranging data fusion is proposed, which integrates the advantages of triangulation and time-of-flight ranging methods, thereby significantly improving reconstruction accuracy and efficiency. Experimental results demonstrate that the proposed algorithm maintains high reconstruction quality even in complex environments, with reconstruction errors controlled within millimeter levels, and reconstruction speed increased by approximately 30% compared to traditional single-ranging methods. Furthermore, to address the issue of data missing from laser rangefinder sensors, deep learning algorithms are introduced for data restoration, further refining the reconstruction model. This research not only provides new ideas and technical support for the application of laser rangefinder sensors in 3D reconstruction but also plays a significant role in promoting the development of 3D reconstruction technology towards higher precision and broader applications.
Keyword:Laser Ranging Sensor Three-Dimensional Reconstruction Multi-Source Data Fusion
目 录
1绪论 1
1.1激光测距传感器与三维重建的背景 1
1.2国内外研究现状综述 1
1.3本文研究方法概述 2
2激光测距传感器原理及特性 2
2.1激光测距基本原理 2
2.2测距精度影响因素分析 3
2.3不同场景下的适用性 3
3三维重建中的数据采集技术 4
3.1数据采集流程设计 4
3.2点云数据获取方法 5
3.3数据预处理与优化 5
4三维重建算法及应用 6
4.1常用重建算法比较 6
4.2算法优化策略探讨 7
4.3实际应用场景分析 7
结论 8
参考文献 9
致谢 10
摘 要
随着三维重建技术在工业检测、虚拟现实、智能机器人等领域的广泛应用，对高精度、高效能的三维数据获取手段需求日益迫切。激光测距传感器凭借其测量精度高、抗干扰能力强等优势成为三维重建的重要工具，本研究旨在深入探讨激光测距传感器在三维重建中的应用技术。通过分析不同场景下激光测距传感器的工作原理与特性，提出了一种基于多源激光测距数据融合的三维重建算法，该算法结合了三角法和飞行时间法两种测距方式的优点，有效提高了重建精度与效率。实验结果表明，所提出的算法在复杂环境下仍能保持较高的重建质量，重建误差控制在毫米级别以内，相较于传统单一测距方法，重建速度提升了约30%。此外，针对激光测距传感器存在的数据缺失问题，引入深度学习算法进行数据修复，进一步完善了重建模型。本研究不仅为激光测距传感器在三维重建中的应用提供了新的思路和技术支持，而且对于推动三维重建技术向更高精度、更广范围发展具有重要意义。
关键词：激光测距传感器 三维重建 多源数据融合
Abstract
With the widespread application of 3D reconstruction technology in fields such as industrial inspection, virtual reality, and intelligent robotics, there is an increasing demand for high-precision and high-efficiency methods of acquiring 3D data. Laser rangefinder sensors have become essential tools for 3D reconstruction due to their advantages of high measurement accuracy and strong anti-interference capability. This study aims to explore the application technologies of laser rangefinder sensors in 3D reconstruction. By analyzing the working principles and characteristics of laser rangefinder sensors under different scenarios, a 3D reconstruction algorithm based on multi-source laser ranging data fusion is proposed, which integrates the advantages of triangulation and time-of-flight ranging methods, thereby significantly improving reconstruction accuracy and efficiency. Experimental results demonstrate that the proposed algorithm maintains high reconstruction quality even in complex environments, with reconstruction errors controlled within millimeter levels, and reconstruction speed increased by approximately 30% compared to traditional single-ranging methods. Furthermore, to address the issue of data missing from laser rangefinder sensors, deep learning algorithms are introduced for data restoration, further refining the reconstruction model. This research not only provides new ideas and technical support for the application of laser rangefinder sensors in 3D reconstruction but also plays a significant role in promoting the development of 3D reconstruction technology towards higher precision and broader applications.
Keyword:Laser Ranging Sensor Three-Dimensional Reconstruction Multi-Source Data Fusion
目 录
1绪论 1
1.1激光测距传感器与三维重建的背景 1
1.2国内外研究现状综述 1
1.3本文研究方法概述 2
2激光测距传感器原理及特性 2
2.1激光测距基本原理 2
2.2测距精度影响因素分析 3
2.3不同场景下的适用性 3
3三维重建中的数据采集技术 4
3.1数据采集流程设计 4
3.2点云数据获取方法 5
3.3数据预处理与优化 5
4三维重建算法及应用 6
4.1常用重建算法比较 6
4.2算法优化策略探讨 7
4.3实际应用场景分析 7
结论 8
参考文献 9
致谢 10
