A fault-tolerant self-organizing flocking approach for UAV aerial survey. (15th October 2017)

• Record Type: Journal Article
• Authors: De Benedetti, M.; D'Urso, F.; Fortino, G.; Messina, F.; Pappalardo, G.; Santoro, C.
• Is Part Of: Journal of network and computer applications. Volume 96(2017)
• Page Start: 14
• Page End: 30
• Publication Date: 2017-10-15
• Subjects: Unmanned aerial vehicles -- Area coverage -- Self-organization -- 3D simulation -- Distributed algorithm; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2017.08.004
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: In this paper we analyze the problem of self-organization for a flock of multirotor UAVs out on a monitoring mission. Such a mission consists in, basically, acquiring data relevant to a certain area of the terrain and transmitting them to a Base Station. To achieve UAV self-organization, we propose a decentralized solution, made highly configurable by tuning a set of parameters intended to model the behavior of the flock and specify the characteristics of the mission. Several aspects are taken into account, such as UAV mutual distances, path planning, dynamic choice of the leader, as well as fault tolerance, which is ensured through a re-scouting of terrain regions, aimed at avoiding data loss due to the failure of one or more UAVs. A further contribution of this work is the design and development of a software tool capable of emulating UAV flight with a high degree of precision and realism. The simulator tool is built on top of the Bullets real-time physics simulation library. Its main purpose is to compute a set of indexes that provide valuable aid both in understanding the real performances of the algorithm, and planning a mission given the set of available resources. Through the analysis of a number of experimental results, we show that, after a suitable tuning of the control parameters, the algorithm succeeds in organizing the flock with a high level of fault tolerance and efficiency, in terms of mission time minimization, low overhead from repeated coverage and inter-UAV message exchange.