论文标题
LOOP-BOX：由单个环闭合触发的多代理直接猛击触发大规模映射
Loop-box: Multi-Agent Direct SLAM Triggered by Single Loop Closure for Large-Scale Mapping
论文作者
论文摘要
在本文中，我们提出了实时大规模3D重建应用程序的多代理框架。在SLAM中，研究人员通常在应用非线性姿势图优化技术后构建和更新3D地图。此外，许多多机构系统普遍使用其他传感器的进程信息。这些方法通常涉及密集的计算机视觉算法，并与各种传感器紧密结合。我们开发了一种基于不同相机系统的多代理3D映射中的键challenging方案的通用方法。提议的框架在第一个循环闭合之间在每个代理的位置方面积极执行。结果表明，所提出的系统仅使用单眼摄像机来产生实时多代理大规模定位和3D全局映射。基于初始匹配，我们的系统可以计算多个3D地图之间的最佳比例差，然后估算大规模全局映射的准确相对姿势转换。
In this paper, we present a multi-agent framework for real-time large-scale 3D reconstruction applications. In SLAM, researchers usually build and update a 3D map after applying non-linear pose graph optimization techniques. Moreover, many multi-agent systems are prevalently using odometry information from additional sensors. These methods generally involve intensive computer vision algorithms and are tightly coupled with various sensors. We develop a generic method for the keychallenging scenarios in multi-agent 3D mapping based on different camera systems. The proposed framework performs actively in terms of localizing each agent after the first loop closure between them. It is shown that the proposed system only uses monocular cameras to yield real-time multi-agent large-scale localization and 3D global mapping. Based on the initial matching, our system can calculate the optimal scale difference between multiple 3D maps and then estimate an accurate relative pose transformation for large-scale global mapping.
