The usage of a completely bio-inspired neuronal model in the navigation of drones is a
challenging process. In this thesis, we propose several neuron models for different drone …

Unmanned aerial vehicles (UAVs) need more autonomy. In light of inherent size, weight and
power (SWaP) constraints, avionics with artificial intelligence implemented using …

The emerging concept of drone swarms creates new opportunities with major societal
implications. However, future drone swarm applications and services pose new …

The autonomous drone race has driven the development of various approaches to agile
flight involving perception, planning and control. The latter is most effective when using …

In autonomous aerial navigation, real-time and energy-efficient obstacle avoidance remains
a significant challenge, especially in dynamic and complex indoor environments. This work …

Drones are used in an increasing number of applications including inspection, environment
mapping, and search and rescue operations. During these missions, they might face …

In recent years, usage of the unmanned aerial vehicle in various fields has developed
rapidly. Drones have the potential to be reliable medical delivery platforms for …

In an attempt to solve search-and-rescue problematics such as rescue time and difficulty in
accessing certain search areas, a cognitive swarm of drones system is proposed, using …

The physically modelled neural and nervous networks pioneered more than two decades
ago by Mark Tilden, EA Rietman and collaborators, M. Ashkenazi et al. have proven to be a …

Because of their ability to naturally float in the air, indoor airships (often called blimps)
constitute an appealing platform for research in aerial robotics. However, when confronted to …