An Explicit Loop Closing Technique for 6D SLAM
An Explicit Loop Closing Technique for 6D SLAM
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发表时间：
2009
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通讯作者：
Jochen Sprickerhof;A. Nüchter;K. Lingemann;J. Hertzberg
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作者：
Jochen Sprickerhof;A. Nüchter;K. Lingemann;J. Hertzberg
同步定位与建图（SLAM）是由移动机器人构建未知环境的地图，同时使用未完成的地图对环境进行导航的问题。对于 SLAM，必须解决两个任务：首先是可靠的特征提取和数据关联，其次是姿态和特征的最佳估计。这两部分通常称为 SLAM 前端和后端。使用激光扫描解决 SLAM 的算法通常依赖于匹配前端部分中的最近点。然后SLAM前端和后端必须迭代以确保地图收敛。本文提出了一种使用 3D 激光距离扫描解决 SLAM 的新方法。我们的目标是避免 SLAM 前端和后端之间的迭代，并提出一种新颖的显式循环闭合启发式（ELCH）。它分离所获取的扫描序列中的最后一次扫描，将其重新关联到迄今为止通过扫描配准构建的地图，并将位姿误差的差异分布在 SLAM 图上。我们在考虑 6 DoF 的 3D 扫描 SLAM 背景下描述 ELCH。使用城市环境的地面实况数据来评估性能。
Simultaneous Localization and Mapping (SLAM) is the problem of building a map of an unknown environment by a mobile robot while at the same time navigating the environment, using the unfinished map. For SLAM, two tasks have to be solved: First reliable feature extraction and data association, second the optimal estimation of poses and features. These two parts are often referred to as SLAM frontend and backend. Algorithms that solve SLAM by using laser scans commonly rely on matching closest points in the frontend part. Then the SLAM frontand backend have to be iterated to ensure that the map converges. This paper presents a novel approach for solving SLAM using 3D laser range scans. We aim at avoiding the iteration between the SLAM frontand backend and propose a novel explicit loop closing heuristic (ELCH). It dissociates the last scan of a sequence of acquired scans, reassociates it to the map, built so far by scan registration, and distributes the difference in the pose error over the SLAM graph. We describe ELCH in the context of SLAM with 3D scans considering 6 DoF. The performance is evaluated using ground truth data of an urban environment.