This article presents a survey of simultaneous localization and mapping (SLAM) and data
fusion techniques for object detection and environmental scene perception in unmanned …

Natural disasters pose significant threats to human life and property, exacerbated by their
sudden onset and increasing frequency. This paper conducts a comprehensive bibliometric …

Efficient data collection methods play a major role in helping us better understand the Earth
and its ecosystems. In many applications, the usage of unmanned aerial vehicles (UAVs) for …

To meet the challenges involved in providing adequate robotic support to first responders, a
holistic approach is needed. This requires close cooperation of first responders, researchers …

Unmanned aerial vehicles (UAVs) equipped with multiple complementary sensors have
tremendous potential for fast autonomous or remote-controlled semantic scene analysis, eg …

Semantic segmentation of oblique unmanned aerial vehicle (UAV) images serves as a
foundation for many modern urban applications, such as road scene monitoring and …

Earthquakes, fire, and floods often cause structural collapses of buildings. However, the
inspection of such damaged buildings poses a high risk for emergency forces or is even …

Over the last two decades, UAVs have become an indispensable acquisition platform in the
remote sensing community. Meanwhile, advanced lightweight sensors have been …

This paper presents an approach to take into account semantic information for autonomous
robot tasks requiring path planning capabilities. A semantic pointcloud or map serves as …

Geometric navigation is nowadays a well-established field of robotics and the research
focus is shifting towards higher-level scene understanding, such as Semantic Mapping …