基于RGB-D视觉的SLAM运动位姿估计-国际计算机科学进展-CSCIED科技核心评价数据库-手机版

基于RGB-D视觉的SLAM运动位姿估计

SLAM motion pose estimation based on RGB-D vision

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DOI	10.12208/j.aics.20250055
刊名	国际计算机科学进展 Advances in International Computer Science
年，卷(期)	2025, 5(3)
作者	刘沛宇^1,3, 盛选禹^1,3, 王广福^1,2,
作者单位	1 季华实验室广东佛山 2 中国煤炭科学研究院矿山人工智能研究院北京 3 清华大学机械工程系北京
摘要	针对三维重建系统使用ORB进行特征的提取并应用快速最近邻进行特征匹配，以及应用Shi-Tomasi角点检测的算法进行特征选择，从而实现位姿估计的数据关联，在此基础上应用ICP算法实现了系统的位姿初步计算。当匹配数对较少，系统基于点到面误差最小化的原则进行位姿计算，并在跟踪失败时进行重定位。这样做的优点是，系统不但可以应对特征丰富的场合，同时也可以处理特征数量较少的场景，提高了系统的鲁棒性。在位姿估计中还应用了单指令多数据流及多线程的支持，提高了运行的实时性能。位姿的初步计算完成后利用捆束优化的方法进行位姿的优化，并通过回环检测降低长时间运行的累积误差，提高了位姿估计的精度。
Abstract	For the 3D reconstruction system, ORB is used for feature extraction, fast nearest neighbor is used for feature matching, and Shi-Tomasi corner detection algorithm is used for feature selection, so as to realize the data association of pose estimation. On this basis, the ICP algorithm is used to achieve Preliminary calculation of the pose of the system. When the matching logarithm is small, the system calculates the pose based on the principle of minimizing the point-to-surface error, and relocates when the tracking fails. The advantage of this is that the system can not only deal with situations with rich features, but also can handle scenes with a small number of features, which improves the robustness of the system. In the pose estimation, the support of single instruction, multiple data streams and multiple threads is also applied, which improves the real-time performance of the operation. After the preliminary calculation of the pose is completed, the bundle optimization method is used to optimize the pose, and the accumulated error of long-time running is reduced through loop detection, and the accuracy of the pose estimation is improved.
关键词	RGB-D；SLAM；特征提取；地图构建；位姿估计
KeyWord	RGB-D; SLAM; Feature extraction; Map construction; Pose estimation
基金项目
页码	34-43

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引用本文

刘沛宇^,, 盛选禹^,, 王广福^,. 基于RGB-D视觉的SLAM运动位姿估计 [J]. 国际计算机科学进展. 2025; 5; (3). 34 - 43.

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