Although point cloud registration has achieved remarkable advances in object-level and
indoor scenes, large-scale registration methods are rarely explored. Challenges mainly …

Mapping an environment is essential for several robotic tasks, particularly for localization. In
this letter, we address the problem of mapping the environment using LiDAR point clouds …

Teams of mobile robots can be employed in many outdoor applications, such as precision
agriculture, search and rescue, and industrial inspection, allowing an efficient and robust …

We focus on the problem of LiDAR point cloud based loop detection (or Finding) and closure
(LDC) for mobile robots. State-of-the-art (SOTA) methods directly generate learned …

Point cloud registration is a crucial task in 3D computer vision. Correspondence-based
methods highly rely on the quality of matching points. However, existing methods still suffer …

Given its wide application in robotics, point cloud registration is a widely researched topic.
Conventional methods aim to find a rotation and translation that align two point clouds in 6 …

The registration of laser point clouds in complex conditions in wilderness scenes is an
important aspect in the research field of autonomous vehicle navigation. It serves as the …

This paper is about 3D pose estimation on LiDAR scans with extremely minimal storage
requirements to enable scalable mapping and localisation. We achieve this by clustering all …

Robots can assist humans in a multitude of ways. For example, robots can handle tedious
tasks that humans prefer not to do, such as vacuum cleaning daily to keep a house clean …

Mobile robots, such as self-driving vehicles, need to operate safely and autonomously in a
wide range of environments. This requires an autonomy software stack with robustness built …