This letter presents an incremental voxel-based lidar-inertial odometry (LIO) method for fast-
tracking spinning and solid-state lidar scans. To achieve the high tracking speed, we neither …

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 Santiago Urban Dataset SUD is a real dataset that combines Mobile Laser
Scanning (MLS) and Handheld Mobile Laser Scanning (HMLS) point clouds. The data is …

Precise localization is critical for autonomous vehicles. We present a self-supervised
learning method that employs transformers for the first time for the task of outdoor …

With the recent development of remote sensing (RS) technology, the amount of RS platforms
has witnessed a substantial increase, and the capacity of Earth observation has been …

Localization is a fundamental task in robotics for autonomous navigation. Existing
localization methods rely on a single input data modality or train several computational …

Urban mobility and safety are critical components of modern city planning, directly impacting
the quality of life for citizens. Efficient transportation systems, including road network …

We propose a lidar odometry and mapping (LOAM) method optimized by the theory of
functional system to map the parking lot and estimate the pose of the ground vehicle in real …

Scene understanding commonly employs vision cameras. Nevertheless, 2D representations
lack the depth information required for 3D world. LiDAR point clouds offer a rich …

A three-dimensional (3-D) point cloud map is a commonly used map type. It is a basis for
many fields, such as localization and navigation. A mobile mapping system (MMS) is a …