Inter-connected objects, either via public or private networks are the near future of modern societies. Such inter-connected objects are referred to as Internet-of-Things (IoT) and or Cyber-Physical Systems (CPS). One example of such a system is based on Unmanned Aerial Vehicles (UAVs). The fleet of such vehicles are prophesied to take on multiple roles involving mundane to high-sensitive, such as, prompt pizza or shopping deliveries to your homes to battlefield deployment for reconnaissance and combat missions. Drones, as we refer to UAVs in this paper, either can operate individually (solo missions) or part of a fleet (group missions), with and without constant connection with the base station. The base station acts as the command centre to manage the activities of the drones. However, an independent, localised and effective fleet control is required, potentially based on swarm intelligence, for the reasons: 1) increase in the number of drone fleets, 2) number of drones in a fleet might be multiple of tens, 3) time-criticality in making decisions by such fleets in the wild, 4) potential communication congestions lag, and 5) in some cases working in challenging terrains that hinders or mandates-limited communication with control centre (i.e., operations spanning long period of times or military usage of such fleets in enemy territory). This self-ware, mission-focused and independent fleet of drones that potential utilises swarm intelligence for a) air-traffic and or flight control management, b) obstacle avoidance, c) self-preservation while maintaining the mission criteria, d) collaboration with other fleets in the wild (autonomously) and e) assuring the security, privacy and safety of physical (drones itself) and virtual (data, software) assets. In this paper, we investigate the challenges faced by fleet of drones and propose a potential course of action on how to overcome them.
In @cite_35 , authors introduced and validated a decentralised architecture for search and rescue missions in ground based robot groups of different sizes. Considered limited communication ability with a command centre and employs distributed communication.
@cite_35
1994253176
Multi-robot systems (MRS) may be very useful on assisting humans in many distributed activities, especially for search and rescue (SaR) missions in hazardous scenarios. However, there is a lack of full distributed solutions, addressing the advantages and limitations along different aspects of team operation, like communication requirements or scalability. In this paper, the effects of distributed group configurations are studied and results are drawn from collective exploration and collective inspection tasks in SaR scenarios, with the aim of understanding the main tradeoffs, and distilling design guidelines of collective architectures. With this purpose, extensive simulation experiments of MRS in a SaR scenario were carried out.