This article surveys recent progress and discusses future opportunities for simultaneous
localization and mapping (SLAM) in extreme underground environments. SLAM in …

This paper reports on the state of the art in underground SLAM by discussing different SLAM
strategies and results across six teams that participated in the three-year-long SubT …

Simultaneous Localization and Mapping (SLAM) is being deployed in real-world
applications, however many state-of-the-art solutions still struggle in many common …

With the increasing affordability of robot technologies and the reduction in size and weight of
autonomous systems, the deployment of autonomous robotic systems on construction sites …

Many existing datasets for lidar place recognition are solely representative of structured
urban environments, and have recently been saturated in performance by deep learning …

Aggressive motions from agile flights or traversing irregular terrain induce motion distortion
in LiDAR scans that can degrade state estimation and mapping. Some methods exist to …

Modern robotic systems are required to operate in challenging environments, which demand
reliable localization under challenging conditions. LiDAR-based localization methods, such …

Global registration is a fundamental task that estimates the relative pose between two
viewpoints of 3D point clouds. However, there are two issues that degrade the performance …

Odometry is crucial for robot navigation, particularly in situations where global positioning
methods like global positioning system are unavailable. The main goal of odometry is to …

Real-time detection of moving objects is an essential capability for robots acting
autonomously in dynamic environments. We thus propose Dynablox, a novel online …