基于视点依赖的局部地图构建高精度三维环境地图
Keyframe-based Dense Mapping with the Graph of View-Dependent Local Maps
- 用视点相关的2D结构存储局部NDT地图，提升近距离精度
- 通过位姿图优化全局地图，闭环检测后可修正误差
- 支持局部地图合并与过滤，适合动态环境建图
本文提出一种新的基于关键帧的映射系统。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），将NDT单元存储在二维视点依赖结构中，更充分地利用了RGB-D相机的特性与不确定性模型，使靠近相机原点的物体以更高精度被表示。局部地图存于位姿图中，可在检测到闭环后进行全局地图修正。同时提出一种合并与滤除局部地图的流程，以生成环境的全局地图。最后与Octomap和NDT-OM进行了对比，并展示了该方法的应用实例。
原文摘要 · Abstract (English)
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.
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