We consider the problem of having a team of Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV) pursue a second team of evaders while concurrently building a map in an unknown environment. We cast the problem in a probabilistic game theoretic framework and consider two computationally feasible greedy pursuit policies: local-max and global-max. To implement this scenario on real UA...

Utilising emerging innovative technologies and systems to improve construction processes in an effort towards digitalisation has been earmarked as critical delivering resilience responsive infrastructure. However, successful implementation is hindered by several challenges. Hence, this study evaluates the challenges facing adoption of unmanned aerial vehicles built environment. The adopted a qu...

This paper presents our framework based on visual exploration of disaster areas (i.e. after an earthquake, a tsunami or an industrial accident). It is meant to help rescue teams to locate hotspots (i.e. half-buried person or broken and dangerous canalization) and to maintain an Internet connection for them. Indeed, our solution uses several small autonomous drones (or UAVs, Unmanned Aerial Vehi...

In this paper I present state-of-art development in vision based autonomous landing of UAVs (Unmanned Aerial Vehicles). I present brief overview of algorithms used to solve this particular problem using vision based control which is very challenging and recent topic of research in the field of computer vision and robotics. After that I compare them based on the achieved results recently by diff...

Title of thesis: DEVELOPMENT OF A REAL-TIME HIERARCHICAL 3D PATH PLANNING ALGORITHM FOR UNMANNED AERIAL VEHICLES Matthew David Solomon, Master of Science, 2016 Thesis directed by: Dr. Huan Xu Department of Aerospace Engineering Unmanned aerial vehicles (UAVs) frequently operate in partially or entirely unknown environments. As the vehicle traverses the environment and detects new obstacles, rap...