Abstract Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …

As a fundamental issue in robotics academia and industry, indoor autonomous mobile
robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information …

Abstract Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. Over the last two decades …

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 …

Accurate and robust localization and mapping are essential components for most
autonomous robots. In this paper, we propose a SLAM system for building globally …

One-shot LiDAR localization refers to the ability to estimate the robot pose from one single
point cloud, which yields significant advantages in initialization and relocalization …

Place recognition is a fundamental topic in computer vision and robotics. It plays a crucial
role in simultaneous localization and mapping (SLAM) systems to retrieve scenes from maps …

Knowledge about the own pose is key for all mobile robot applications. Thus pose
estimation is part of the core functionalities of mobile robots. In the last two decades, LiDAR …

Meticulous 3D environment representations have been a longstanding goal in computer
vision and robotics fields. The recent emergence of neural implicit representations has …

Reconstructing large-scale 3D scenes is essential for autonomous vehicles, especially
when partial sensor data is lost. Although the recently developed neural radiance fields …