This work presents a review and discussion of the challenges that must be solved in order to
successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From …

In recent years, since researchers began to study on Unmanned Aerial Vehicles (UAVs),
UAVs have been integrated into today's everyday life, including civilian area and military …

Today's autonomous drones have reaction times of tens of milliseconds, which is not
enough for navigating fast in complex dynamic environments. To safely avoid fast moving …

This paper deals with deep neural networks for predicting accurate dense disparity map with
Semi-global matching (SGM). SGM is a widely used regularization method for real scenes …

Unmanned Aerial Vehicles have undergone rapid developments in recent decades. This
has made them very popular for various military and civilian applications allowing us to …

Micro Aerial Vehicles (FOV) are very suitable for flying in indoor environments, but
autonomous navigation is challenging due to their strict hardware limitations. This paper …

In this paper, we propose a novel method to predict the correctness of stereo
correspondences, which we call confidence, and a confidence fusion method for dense …

For intelligent quadcopter UAVs, a robust and reliable autonomous planning system is
crucial. Most current trajectory planning methods for UAVs are suitable for static …

Drones have the potential to revolutionize power line inspection by increasing productivity,
reducing inspection time, improving data quality, and eliminating the risks for human …

Deploying autonomous robots in crowded indoor environments usually requires them to
have accurate dynamic obstacle perception. Although plenty of previous works in the …