Autonomous exploration of subterranean environments constitutes a major frontier for
robotic systems as underground settings present key challenges that can render robot …

We present an efficient multi-sensor odometry system for mobile platforms that jointly
optimizes visual, lidar, and inertial information within a single integrated factor graph. This …

Integration of multiple sensor modalities and deep learning into Simultaneous Localization
And Mapping (SLAM) systems are areas of significant interest in current research. Multi …

Falls among the elderly population cause detrimental physical, mental, financial problems
and, in the worst case, death. The increasing number of people entering the higher risk age …

High accuracy 3D surface information is required for many construction robotics tasks such
as automated cement polishing or robotic plaster spraying. However, consumer-grade depth …

To cope with the growing demand for transportation on the railway system, accurate, robust,
and high-frequency positioning is required to enable a safe and efficient utilization of the …

In this paper, we propose a robust end-to-end multi-modal pipeline for place recognition
where the sensor systems can differ from the map building to the query. Our approach …

The capabilities of discovering new knowledge and updating the previously acquired one
are crucial for deploying autonomous robots in unknown and changing environments …

Data fusion algorithms that employ LiDAR measurements, such as Visual-LiDAR, LiDAR-
Inertial, or Multiple LiDAR Odometry and simultaneous localization and mapping (SLAM) …

Because of the high complementarity between global navigation satellite systems (GNSSs)
and visual-inertial odometry (VIO), integrated GNSS-VIO navigation technology has been …