Robust and accurate visual localization is a fundamental capability for numerous
applications, such as autonomous driving, mobile robotics, or augmented reality. It remains …

Place recognition in 3D data is a challenging task that has been commonly approached by
adapting image-based solutions. Methods based on local features suffer from ambiguity and …

Recently, autonomous mobile robots have gained popularity in the modern world due to
their relevance technology and application in real world situations. The global market for …

Highly accurate and robust localization ability is of great importance for autonomous
vehicles (AVs) in urban scenarios. Traditional vision-based methods suffer from lost due to …

We present the DLR Planetary Stereo, Solid-State LiDAR, Inertial (S3LI) dataset, recorded
on Mt. Etna, Sicily, an environment analogous to the Moon and Mars, using a hand-held …

We present a visual localization framework based on novel deep attention aware features
for autonomous driving that achieves centimeter level localization accuracy. Conventional …

Recent advances in image description and matching allowed significant improvements in
Visual Place Recognition (VPR). The wide variety of methods proposed so far and the …

Localization and Simultaneous Localization and Mapping (SLAM) is a fundamental module
in any Autonomous vehicle or Autonomous Mobile Robot. In order for an autonomous …

Visual place recognition (VPR) is the problem of recognising a previously visited location
using visual information. Many attempts to improve the performance of VPR methods have …

Self-localization is a crucial requirement for visual robot place recognition. Particularly, the
3D point cloud obtained from 3D laser rangefinders (LRF) is applied to it. The critical part is …