RGB-D data-based Simultaneous Localization and Mapping (RGB-D SLAM) aims to
concurrently estimate robot poses and reconstruct traversed environments using RGB-D …

We present a stereo-based dense mapping algorithm for large-scale dynamic urban
environments. In contrast to other existing methods, we simultaneously reconstruct the static …

Map-based localization and sensing are one of the key components in autonomous driving
technologies, where high quality 3D map reconstruction is fundamentally utmost important …

We present a simple yet highly efficient method to eliminate spurious trails of dynamic
objects for 3-D point cloud map updating. First, we extract the view overlaps based on view …

Simultaneous localization and mapping (SLAM) technology is a research hotspot in the field
of intelligent mobile robot, and many researchers have developed many classic systems in …

Mobile mapping, in particular, Mobile Lidar Scanning (MLS) is increasingly widespread to
monitor and map urban scenes at city scale with unprecedented resolution and accuracy …

With the continuous progress of science and technology, the dense point cloud mapping has
gradually replaced the traditional laser mapping and sparse point cloud mapping because …

Indoor mapping attracts more attention with the development of 2D and 3D camera and
Lidar sensor. Lidar systems can provide a very high resolution and accurate point cloud …

We present a simple yet highly efficient method to eliminate spurious trails of dynamic
objects for 3D point cloud map updating. Firstly, we extract the view overlaps based on view …

«What is around me?» knowing how to answer to this question is essential for a robot to
navigate safely in its environment. In this part, we will try to find some answers by introducing …