SLAM-Loop Closing with Visually Salient Features
SLAM-Loop Closing with Visually Salient Features
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DOI：
10.1109/robot.2005.1570189
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发表时间：
2005-04
期刊：
影响因子：
--
通讯作者：
P. Newman;K. Ho
中科院分区：
文献类型：
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作者：
P. Newman;K. Ho
在同步定位和地图绘制（SLAM）的背景下，“闭环”是决定车辆在任意长度的偏移之后是否已经返回到先前访问的区域的任务。可靠的闭环既重要又困难。毫无疑问，这是长期、强大的SLAM的最大障碍之一。本文说明了如何视觉功能，结合扫描激光数据，可以使用到一个很大的优势。我们使用的视觉显着性的概念，集中选择合适的（仿射不变）图像特征描述符存储在数据库中。当查询最近拍摄的图像时，数据库返回匹配图像的拍摄时间。该时间信息用于发现循环关闭事件。重要的是，这是独立于估计的地图和车辆位置来实现的。我们将上述技术集成到SLAM算法中，该算法使用延迟车辆状态和扫描匹配来形成非线性几何约束。我们目前的初步结果，使用该系统在室内环境中关闭循环（约100米）。
Within the context of Simultaneous Localisation and Mapping (SLAM), “loop closing” is the task of deciding whether or not a vehicle has, after an excursion of arbitrary length, returned to a previously visited area. Reliable loop closing is both essential and hard. It is without doubt one of the greatest impediments to long term, robust SLAM. This paper illustrates how visual features, used in conjunction with scanning laser data, can be used to a great advantage. We use the notion of visual saliency to focus the selection of suitable (affine invariant) image-feature descriptors for storage in a database. When queried with a recently taken image the database returns the capture time of matching images. This time information is used to discover loop closing events. Crucially this is achieved independently of estimated map and vehicle location. We integrate the above technique into a SLAM algorithm using delayed vehicle states and scan matching to form interpose geometric constraints. We present initial results using this system to close loops (around 100m) in an indoor environment.