Today's mobile robots are expected to operate in complex environments they share with
humans. To allow intuitive human-robot collaboration, robots require a human-like …

The demand for digitizing manufacturing and controlling processes has been steadily
increasing in recent years. Digitization relies on different techniques and equipment, which …

We introduce RoomsSeg, a novel method for segmenting occupancy grid maps into regions
that represent rooms and corridors in the real world. The segmentation is utilized for …

In this work, we research and evaluate the usage of convolutional variational auto-encoders
for end-to-end learning of semantic-metric occupancy grids from monocular data. The …

Autonomous driving is, besides electrification, currently one of the most competitive areas in
the automotive industry. A substantially challenging part of autonomous vehicles is the …

With the rapid development of artificial intelligence technology, indoor mobile robots are
widely applied in human's daily life. Traditional SLAM-based methods mostly rely on low …

Elements from cognitive psychology have been applied in a variety of ways to artificial
intelligence. One of the lesser studied areas is in how episodic memory can assist learning …

This work focuses on how to compute trajectories for an autonomous wheelchair based on
indoor GIS maps, in particular on IndoorGML maps, which set the standard in this context …

With the increasingly complex application scenarios of indoor mobile robots, traditional
navigation methods based on metric maps have been unable to meet people's needs …

Creating and maintaining an accurate representation of the environment is an essential
capability for every mobile robot. Especially, semantic information plays an important role in …