Localization is a crucial component for the navigation of autonomous vehicles. It
encompasses global localization and place recognition, allowing a system to identify …

LiDAR-based SLAM is a core technology for autonomous vehicles and robots. Despite the
intense research activity in this field, each proposed system uses a particular sensor post …

This article introduces BEVPlace++, a novel, fast, and robust LiDAR global localization
method for unmanned ground vehicles. It uses lightweight convolutional neural networks …

Forests play a crucial role in our ecosystems, functioning as carbon sinks, climate stabilizers,
biodiversity hubs, and sources of wood. By the very nature of their scale, monitoring and …

Robust and accurate point cloud registration is an essential part of many robotic tasks such
as SLAM or object pose retrieval. In this paper, we address the problem of global 3D point …

Constructing precise global maps is a key task in robotics and is required for localization,
surveying, monitoring, or constructing digital twins. To build accurate maps, data from mobile …

While global point cloud registration systems have advanced significantly in all aspects,
many studies have focused on specific components, such as feature extraction, graph …

Imaging radar is an emerging sensor modality in the context of Localization and Mapping
(SLAM), especially suitable for vision-obstructed environments. This article investigates the …