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李子宽, 魏明强, 吴巧云, 郭延文, 徐凯, 李嘉, 汪俊. 球谐算子驱动三维激光SLAM闭环检测[J]. 计算机辅助设计与图形学学报.
引用本文: 李子宽, 魏明强, 吴巧云, 郭延文, 徐凯, 李嘉, 汪俊. 球谐算子驱动三维激光SLAM闭环检测[J]. 计算机辅助设计与图形学学报.
Loop Closure Detection in 3D Laser-based SLAM using Spherical Harmonics Descriptors[J]. Journal of Computer-Aided Design & Computer Graphics.
Citation: Loop Closure Detection in 3D Laser-based SLAM using Spherical Harmonics Descriptors[J]. Journal of Computer-Aided Design & Computer Graphics.

球谐算子驱动三维激光SLAM闭环检测

Loop Closure Detection in 3D Laser-based SLAM using Spherical Harmonics Descriptors

  • 摘要: 闭环检测是三维激光SLAM实现自主定位和导航的核心环节. 针对目前闭环检测存在高复杂度及低准确度的难题, 提出了具有旋转不变性的球谐算子SHE与绕Z轴旋转不变的球谐算子SHZE; 结合SHE和SHZE的优势, 通过两步搜索提出了一种新颖的三维激光SLAM闭环检测算法SH-LCD. SH-LCD在提高信息丰富度的同时降低了闭环检测计算的复杂度, 具有较强的特征提取能力与普适性. 在KITTI, NCLT, Complex Urban这三个公共基准数据集上的闭环检测实验表明, SH-LCD闭环检测精度优于最新的闭环检测方法, 包括: Scan Context, M2DP, OverlapNet等. 此外, SH-LCD闭环检测效率高, 计算算子与算子匹配消耗的时间仅需约12.0 ms和2.3 ms, 满足SLAM实时性的要求.

     

    Abstract: Loop closure detection is the core of 3D laser-based SLAM to realize autonomous positioning and naviga-tion. Aiming at the problems of high complexity and low accuracy in current loop closure detection, a spherical harmonic energy with rotation invariance (SHE) and a spherical harmonic energy with the z-axis rotation invariance (SHZE) are first proposed in this paper. Combining the advantages of SHE and SHZE via a "two-step search", a novel loop closure detection algorithm for 3D laser-based SLAM, denoted as SH-LCD, is proposed. SH-LCD not only improves the richness of information extraction, but also reduces the computation complexity of loop closure detection, thus characterized by strong feature extraction ability and universality. Extensive loop closure detection evaluations on benchmark datasets including KITTI, NCLT, and Complex Urban, demonstrate that the detection accuracy of SH-LCD significantly outperforms the current state-of-the-art methods including Scan Context, M2DP, OverlapNet, etc. In addition, the efficiency of SH-LCD is high, and the time for operator calculation and operator matching are about 12.0 ms and 2.3 ms, respectively. This meets the real-time requirements of SLAM.

     

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