Supervision, Control and Learning for Intelligent Robot Systems

Multirotor drones are becoming increasingly popular in a number of application fields, with a unique appeal to the scientific community and the general public. Applications include security, monitoring and surveillance, environmental mapping, and emergency scenario management: in all these areas, two of the main issues to address are the availability of appropriate software architectures to coordinate teams of drones and solutions to cope with the short-term battery life. This article proposes the novel concepts of Social Drone Sharing (SDS) and Social Charging Station (SCS), which provide the basis to address these problems. Specifically, the article focuses on teams of drones in pre- and post-event monitoring and assessment. Using multirotor drones in these situations can be difficult due to the limited flight autonomy when multiple targets need to be inspected. The idea behind the SDS concept is that citizens can volunteer to recharge a drone or replace its batteries if it lands on their property. The computation of paths to inspect multiple targets will then take into account the availability of SCSs to find solutions compatible with the required inspection and flight times. The main contribution of this article is the development of a cloud-based software architecture for SDS mission management, which includes a multi-drone path-optimization algorithm taking the SDS and SCS concepts into account. Experiments in simulation and a lab environment are discussed, paving the path to a larger trial in a real scenario.