In this article, we propose a new keyframe-based mapping system. The proposed method updates local Normal Distribution Transform maps (NDT) using data from an RGB-D sensor. The cells of the NDT are stored in 2D view-dependent structures to better utilize the properties and uncertainty model of RGB-D cameras. This method naturally represents an object closer to the camera origin with higher precision. The local maps are stored in the pose graph which allows correcting global map after loop closure detection. We also propose a procedure that allows merging and filtering local maps to obtain a global map of the environment. Finally, we compare our method with Octomap and NDT-OM and provide example applications of the proposed mapping method.

翻译：本文提出一种新的基于关键帧的建图系统。该方法利用RGB-D传感器数据更新局部正态分布变换地图（NDT）。NDT的栅格单元存储于二维视图依赖结构中，以更好地利用RGB-D相机的特性与不确定性模型。该方法天然地以更高精度表示靠近相机原点的物体。局部地图存储于位姿图中，可在检测到回环闭合后修正全局地图。我们还提出一种允许合并与过滤局部地图以获取环境全局地图的流程。最后，我们将本方法与Octomap及NDT-OM进行对比，并展示所提建图方法的示例应用。