4 accepted papers
In this letter, we present a distributed algorithm for flocking in complex environments that operates at constant altitude, without explicit communication, no a priori information about the environment, and by using only on-board sensing and computation capabilities. We provide sufficient conditions
The compact flocking of relatively localized Un-manned Aerial Vehicles (UAVs) in high obstacle density areas is discussed in this paper. The presented work tackles realistic scenarios in which the environment map is not known apriori and the use of a global localization system and communication infr…
By leveraging our relative Micro-scale Unmanned Aerial Vehicle localization sensor UVDAR, we generated an automatically annotated dataset MIDGARD, which the community is invited to use for training and testing their machine learning systems for the detection and localization of Microscale Unmanned A…
A novel onboard relative localization method, based on ultraviolet light, used for real-time control of a leader-follower formation of multirotor UAVs, is presented in this paper. A new smart sensor, UVDAR, is employed in an innovative way, which does not require communication and is extremely relia