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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
and robustness of a network of remotely or autonomous
vehicles involved in monitoring and security applications in
the maritime domain. The discussion tackles this topic modeling the
network of marine vehicles as a complex system characterized by a
mix of high and low level issues, in which high-level operations rely
on low-level ones and vice-versa.
The high level issues faced in this dissertation includes mission
planning operations for a network of moving assets. The availability
of heterogeneous data of different nature about the area of interest
is exploited to generate risk maps. As first result, these produce an
accurate situation awareness of the area of interest describing which
sub-areas may require a deeper coverage. Then, the subsequent integration
of such maps in planning system produces as result the
execution of planning operations in a more effective way. This thesis
presents the application of this approach in the scenario of counterpiracy
operations.
Within the high level issues, this dissertation presents a systematic
approach for the design and early assessment of the performance of a
surveillance network for the protection of a high value asset against
asymmetric threat. The problem is tackled through a game theoretic
formalism as a potential game to incorporate in a mathematical
representation the strategy pursued by surveillance operators during
operative scenarios. The approach is evaluated through Monte Carlo
simulations and performance of the approach is provided in terms
of a security index that allows to obtain a tool for team sizing. The
tool provides the minimum number of marine vehicles to be used in
the system, given a desired security level to be guaranteed and the
maximum threat velocity.
Finally, within low level issues, this thesis presents the simulative
results and algorithmic developments of the task-priority based control
applied to a distributed sampling network in an area coverage
and adaptive sampling mission scenario. The proposed approach allows
the fulfillment of a chain of tasks with decreasing priority each
of which directly related to both operability and safety aspects of the
entire mission. The task-priority control is presented both in the centralized
and decentralized implementations showing a comparison
of performance. Finally simulations of the adaptive sampling mission
scenario are provided showing the effectiveness of the proposed
solution.
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