ETD system

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Tesi etd-05102018-110503


Thesis type
Tesi di dottorato di ricerca
Author
FABBRI, TOMMASO
URN
etd-05102018-110503
Title
DISTRIBUTED MONITORING AND SECURITY SYSTEMS WITH AUTONOMOUS MARINE VEHICLES
Settore scientifico disciplinare
ING-INF/04
Corso di studi
INGEGNERIA DELL'INFORMAZIONE
Commissione
tutor Prof. Caiti, Andrea
commissario Prof. Vicen, Raul
commissario Prof. Di Lizia, Pierluigi
Parole chiave
  • autonomous vehicles
  • distributed systems
  • control systems
Data inizio appello
19/05/2018;
Consultabilità
parziale
Data di rilascio
19/05/2021
Riassunto analitico
THIS thesis has the main goal of contribute to increase the reliability<br>and robustness of a network of remotely or autonomous<br>vehicles involved in monitoring and security applications in<br>the maritime domain. The discussion tackles this topic modeling the<br>network of marine vehicles as a complex system characterized by a<br>mix of high and low level issues, in which high-level operations rely<br>on low-level ones and vice-versa.<br>The high level issues faced in this dissertation includes mission<br>planning operations for a network of moving assets. The availability<br>of heterogeneous data of different nature about the area of interest<br>is exploited to generate risk maps. As first result, these produce an<br>accurate situation awareness of the area of interest describing which<br>sub-areas may require a deeper coverage. Then, the subsequent integration<br>of such maps in planning system produces as result the<br>execution of planning operations in a more effective way. This thesis<br>presents the application of this approach in the scenario of counterpiracy<br>operations.<br>Within the high level issues, this dissertation presents a systematic<br>approach for the design and early assessment of the performance of a<br>surveillance network for the protection of a high value asset against<br>asymmetric threat. The problem is tackled through a game theoretic<br>formalism as a potential game to incorporate in a mathematical<br>representation the strategy pursued by surveillance operators during<br>operative scenarios. The approach is evaluated through Monte Carlo<br>simulations and performance of the approach is provided in terms<br>of a security index that allows to obtain a tool for team sizing. The<br>tool provides the minimum number of marine vehicles to be used in<br>the system, given a desired security level to be guaranteed and the<br>maximum threat velocity.<br>Finally, within low level issues, this thesis presents the simulative<br>results and algorithmic developments of the task-priority based control<br>applied to a distributed sampling network in an area coverage<br>and adaptive sampling mission scenario. The proposed approach allows<br>the fulfillment of a chain of tasks with decreasing priority each<br>of which directly related to both operability and safety aspects of the<br>entire mission. The task-priority control is presented both in the centralized<br>and decentralized implementations showing a comparison<br>of performance. Finally simulations of the adaptive sampling mission<br>scenario are provided showing the effectiveness of the proposed<br>solution.
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