Localization algorithms that rely on 3D LiDAR scanners often encounter temporary failures
due to various factors, such as sensor faults, dust particles, or drifting. These failures can …

Multiple modern robotic applications benefit from centralized cognition and processing
schemes. However, modern equipped robotic platforms can output a large amount of data …

This paper presents a framework addressing the challenge of global localization in
autonomous mobile robotics by integrating LiDAR-based descriptors and Wi-Fi finger …

Change detection and irregular object extraction in 3D point clouds is a challenging task that
is of high importance not only for autonomous navigation but also for updating existing …

In the field of resource-constrained robots and the need for effective place recognition in
multi-robotic systems, this article introduces RecNet, a novel approach that concurrently …

A robust, resource-efficient, distributed, and minimally parameterized 3D map matching and
merging algorithm is proposed. The suggested algorithm utilizes tomographic features from …

In this article, a novel approach for merging 3D point cloud maps in the context of egocentric
multi-robot exploration is presented. Unlike traditional methods, the proposed approach …

In this article, we perform a novel and extended field evaluation of the state-of-the-art
algorithmic frameworks' performance on global pose estimation. More specifically, we focus …

Notation conventions for rigid transformations are as diverse as they are fundamental to the
field of robotics. A well-defined convention that is practical, consistent and unambiguous is …