Scientists of the doctoral school “Networked Autonomous Aerial Vehicles” implemented a self-adaptive swarm of drones and showcased it in Klagenfurt’s new drone hall, one of the largest and most modern facilities of its kind.
A workshop about communication in swarms took place in Klagenfurt in mid-July. Invited speakers and other experts discussed questions at the interface of robotics, distributed systems, and communication technology.
The swarmalator model for systems in which synchronization and swarming are coupled is implemented and studied for the first time in a technical system.
Wherever several clocks tick simultaneously, it is tricky to get them all to display precisely the same time. This can be a challenge for drone swarms that are airborne together. To tackle this problem, young scientist Agata Barciś is developing new technologies.
A multidisciplinary team at the University of Klagenfurt is due to deliver initial insights on the efficient operation of a drone-based delivery network. Doctoral student Pasquale Grippa will present the results at the Robotics: Science and Systems event taking place at MIT this week.
An interdisciplinary workshop on self-organization and swarm intelligence in cyber physical systems was held at Lakeside Labs this week. Experts presented their work and discussed open issues in this exciting field.
Lakeside Labs is a non-profit organization for scientific research and development of self-organizing networked systems. Our goal is to apply and improve self-organization in the areas of IoT, robotics and transportation. It has been a successful year.
Mobile robots in explorer missions need to charge their batteries from time to time. Different policies for coordinated recharging in teams of robots are evaluated.
Synchronization algorithms based on the theory of pulse-coupled oscillators are evaluated on programmable radios. It is experimentally demonstrated that the stochastic nature of coupling is a key ingredient for convergence to synchrony. We propose a distributed algorithm for automatic phase rate equalization and show that synchronization precisions below one microsecond are possible.
The convergence of binary majority consensus algorithms is studied in networks with different types of disturbances. It is shown how randomization can foster convergence.