  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.
