Guido de Croon
Received his M.Sc. and Ph.D. in the field of Artificial Intelligence (AI) at Maastricht University, the Netherlands. His research interest lies with computationally efficient algorithms for robot autonomy, with an emphasis on computer vision. Since 2008 he has worked on algorithms for achieving autonomous flight with small and light-weight flying robots, such as the DelFly flapping wing MAV. In 2011-2012, he was a research fellow in the Advanced Concepts Team of the European Space Agency, where he studied topics such as optical flow based control algorithms for extraterrestrial landing scenarios. Currently, he is associate professor at TU Delft and scientific lead of the Micro Air Vehicle lab (MAV-lab) of Delft University of Technology, where he works with his group towards swarms of autonomously flying tiny robots.
Towards swarms of small flying robots
Swarm robotics holds great potential for real-world applications, promising the swift and robust execution of tasks that would be difficult to achieve by a single robot. Small flying robots in principle lend themselves well to this concept. A single, light-weight flying robot is extremely limited in terms of the sensors and processing that can be carried onboard, while successfully flying around requires continuous, quick reactions to the environment. In this presentation, I will discuss the work I performed with my group on the way to realizing a group of light-weight (< 50g) flying robots that are to explore an unknown environment for a search-and-rescue mission. I will delve into the type of artificial intelligence that we give to the robots, and how we achieved to let them sense where neighboring robots are. Sensing other robots in a local neighborhood is a very common and fundamental assumption of much of the theoretical work in the area of swarm algorithms, but is very hard to achieve on small flying robots. Finally, I will describe the remaining major challenges on the road towards swarms of small flying robots.