With the growing availability of extensive 3D datasets and the rapid progress in
computational power, deep learning (DL) has emerged as a highly promising approach for …

Mobile robots navigating in outdoor environments frequently encounter the issue of
undesired traces left by dynamic objects and manifested as obstacles on map, impeding …

Abstract Three-dimensional (3D) mapping is important to achieve early warning for
construction safety and support the long-term safety maintenance of tunnels. However …

Three-dimensional point cloud map plays an important role in 3-D reconstruction,
autonomous robot navigation, autonomous driving, and environmental monitoring …

Dynamic objects diversify the distribution of point cloud in the map, degrading the
performance of the robotic downstream tasks. To address this problem, we present a novel …

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 …

Point cloud maps generated via LiDAR sensors using extensive remotely sensed data are
commonly used by autonomous vehicles and robots for localization and navigation …

Localization and navigation of vehicles using 3D point cloud maps is an important strategy
in autonomous driving. In this work, we propose a new method for offline building static …

State estimation and mapping are vital prerequisites for autonomous vehicle intelligent
navigation. However, maintaining high accuracy in urban environments remains …

Simultaneous localization and mapping (SLAM) employing 3-D light detection and ranging
(LiDAR) data constitutes an indispensable perception technology for geospatial sensing of …