Abstract
This paper deals with the design of a guidance control system for a swarm of unmanned aerial systems flying at a given altitude, addressing flight formation requirements that can be formulated constraining the swarm to be on the nodes of a triangular mesh. Three decentralized guidance algorithms are presented. A classical fixed leader–follower scheme is compared with two alternative schemes: the former is based on the self-identification of one or more time-varying leaders; the latter is an algorithm without leaders. Several operational scenarios have been simulated involving swarms with obstacles and an increasing number of aircraft in order to prove the effectiveness of the proposed guidance schemes.
Highlights
D’Amato, E.; Mattei, M.; Notaro, I.In the last decade, research on civil unmanned aerial systems has been growing due to their great versatility and adaptability to several kinds of missions and lower operating costs as well
Some oscillations can be observed in the trajectories, even far from the obstacles, that are better damped in the no leader scheme
Three decentralized guidance systems based on different Unmanned Aerial Vehicle (UAV) formation control schemes are presented
Summary
The components of a team can simultaneously collect information from multiple locations, reducing the time needed to acquire all the data necessary for decision-making, or they can take actions in multiple locations, reducing the reaction time Another important feature is related to the complementarity of flight formation members; for example, the efficiency of the system can be improved by distributing different sensors on multiple UAVs, reducing payload and, in the case of redundancy, increasing at the same time the robustness of the whole system, no longer related to the reliability of a single aircraft. A real improvement can be achieved if all the aircraft can properly collaborate to accomplish the mission target by coordinating their tasks Within this frame, an extensive research field focuses on the swarming behavior, or flocking, known in nature as the collective behavior of a large number of agents able to interact and share a common.
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