论文标题
强度扫描上下文：编码强度和几何关系，用于循环闭合检测
Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure Detection
论文作者
论文摘要
循环闭合检测是同时定位和映射（SLAM）的必不可少且具有挑战性的问题。由于其视图和照明不变特性，通常通过光检测和范围（LIDAR）传感器对其进行处理。 3D回路闭合检测的现有作品通常利用局部或全局几何描述符的匹配，但没有考虑强度读数。在本文中，我们探讨了LiDAR扫描的强度属性，并表明它可以有效地识别位置。具体而言，我们提出了一种新型的全局描述符，强度扫描上下文（ISC），探索了几何和强度特征。为了提高环路闭合检测的效率，提出了有效的两阶段分层重新识别过程，包括基于二进制操作的快速几何关系检索和强度结构的重新识别。已经进行了包括本地实验和公共数据集测试在内的彻底实验，以评估所提出的方法的性能。与现有的仅几何方法相比，我们的方法达到更高的召回率和召回精度。
Loop closure detection is an essential and challenging problem in simultaneous localization and mapping (SLAM). It is often tackled with light detection and ranging (LiDAR) sensor due to its view-point and illumination invariant properties. Existing works on 3D loop closure detection often leverage the matching of local or global geometrical-only descriptors, but without considering the intensity reading. In this paper we explore the intensity property from LiDAR scan and show that it can be effective for place recognition. Concretely, we propose a novel global descriptor, intensity scan context (ISC), that explores both geometry and intensity characteristics. To improve the efficiency for loop closure detection, an efficient two-stage hierarchical re-identification process is proposed, including a binary-operation based fast geometric relation retrieval and an intensity structure re-identification. Thorough experiments including both local experiment and public datasets test have been conducted to evaluate the performance of the proposed method. Our method achieves higher recall rate and recall precision than existing geometric-only methods.
