Long‐term operation of robots creates new challenges to Simultaneous Localization and
Map** (SLAM) algorithms. Long‐term SLAM algorithms should adapt to recent changes …

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 …

Most autonomous driving solutions require some method of localization within their
environment. Typically, onboard sensors are used to localize the vehicle precisely in a …

Map** and localization using surface features is prone to failure due to environment
changes such as inclement weather. Recently, Localizing Ground Penetrating Radar …

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 …

Map** and localization using surface features is prone to failure due to environment
changes such as inclement weather. Recently, Localizing Ground Penetrating Radar …

Abstract Changes in appearance present a tremendous problem for the visual localization of
an autonomous vehicle in outdoor environments. Data association between the current …

In visual place recognition (VPR), map segmentation (MS) is a preprocessing technique
used to partition a given view-sequence map into place classes (ie, map segments) so that …

Autonomous navigation in underwater environments presents challenges due to factors
such as light absorption and water turbidity, limiting the effectiveness of optical sensors …