Autonomous systems will play an essential role in many applications across diverse
domains including space, marine, air, field, road, and service robotics. They will assist us in …

We present an extensive comparison between three topometric localization systems: radar-
only, lidar-only, and a cross-modal radar-to-lidar system across varying seasonal and …

Challenges inherent to autonomous wintertime navigation in forests include lack of reliable
a Global Navigation Satellite System (GNSS) signal, low feature contrast, high illumination …

In this letter, we learn visual features that we use to first build a map and then localize a
robot driving autonomously across a full day of lighting change, including in the dark. We …

For robots navigating using only a camera, illumination changes in indoor environments can
cause re-localization failures during autonomous navigation. In this paper, we present a …

We present BioSLAM, a lifelong (lifelong simultaneous localization and mapping) SLAM
framework for learning various new appearances incrementally and maintaining accurate …

In this paper, we compare different map management techniques for long-term visual
navigation in changing environments. In this scenario, the navigation system needs to …

Nowadays, most agricultural robots rely on precise and expensive localisation, typically
based on global navigation satellite systems (GNSS) and real-time kinematic (RTK) …

When a mobile robot is asked to navigate intelligently in an environment, it needs to
estimate its own and the environment's state. One of the popular methods for robot state and …

The performance of deep neural networks and the low costs of computational hardware has
made computer vision a popular choice in many robotic systems. An attractive feature of …