In the process of urban environment mapping, the sequential accumulations of dynamic objects will leave a large number of traces in the map. These traces will usually have bad influences on the localization accuracy and navigation performance of the robot. Therefore, dynamic objects removal plays an important role for creating clean map. However, conventional dynamic objects removal methods usually run offline. That is, the map is reprocessed after it is constructed, which undoubtedly increases additional time costs. To tackle the problem, this paper proposes a novel method for online dynamic objects removal for ground vehicles. According to the observation time difference between the object and the ground where it is located, dynamic objects are classified into two types: suddenly appear and suddenly disappear. For these two kinds of dynamic objects, we propose downward retrieval and upward retrieval methods to eliminate them respectively. We validate our method on SemanticKITTI dataset and author-collected dataset with highly dynamic objects. Compared with other state-of-the-art methods, our method is more efficient and robust, and reduces the running time per frame by more than 60$\%$ on average.

翻译：在城市环境建图过程中，动态物体的连续累积会在地图中留下大量轨迹。这些轨迹通常会对机器人的定位精度与导航性能产生不良影响。因此，动态物体移除对于创建洁净地图具有重要作用。然而，传统的动态物体移除方法通常以离线方式运行，即在地图构建完成后对其进行后处理，这无疑增加了额外的时间成本。为解决该问题，本文提出一种面向地面车辆的在线动态物体移除新方法。根据物体与其所处地面的观测时间差，将动态物体分为两类：突然出现型与突然消失型。针对这两类动态物体，我们分别提出向下检索与向上检索方法以消除它们。我们在SemanticKITTI数据集及作者采集的高动态物体数据集上验证了本方法。与其他先进方法相比，本方法具有更高的效率与鲁棒性，平均每帧运行时间降低超过60$\%$。