PhD Thesis

Juri Khanmeh. Task-Based Motion Control of an Autonomous Surface Vehicle in a Combined System with a Remotely Operated Vehicle (ASV–ROV).
Ph.D. Thesis, University of Genova, 2026.
Abstract Marine robotics plays a crucial role in carrying out a wide range of complex underwater missions. In this context, tethered Remotely Operated Vehicles (ROVs) provide several advantages, including efficient data transmission and a reliable physical connection that ensures safety in emergency situations. However, their operational range is inherently limited by the length of the tether. This study investigates the possibility of extending the operational range of ROVs by introducing a novel control strategy that enables cooperative operation with an Autonomous Surface Vehicle (ASV). The proposed ASV–ROV system addresses two primary challenges: the restricted mobility of the ROV and the potential risk of cable entanglement. To mitigate these issues, a new control framework is developed to ensure smooth ROV motion while minimizing conditions that could lead to tether entanglement. The control system allows the ASV to maintain alignment with the ROV and preserve a desired distance, while simultaneously regulating the length of cable deployed in the water. This thesis presents the control design of the ASV motion for a cooperative navigation with the ROV. The work includes the formulation of a novel control strategy that enables the ASV to autonomously track and follow the ROV while avoiding obstacles and adjusting its trajectory to maintain safe and efficient cooperation. The proposed control framework is validated through comprehensive software-in-the-loop simulations that represents offshore wind farm environments. The numerical results demonstrate the effectiveness and robustness of the system in improving cooperative navigation performance, reducing power consumption, and enhancing operational resilience under dynamic marine conditions. Furthermore, the work of this thesis investigates the impact of tether management on the overall stability and energy efficiency of the ASV–ROV system. An analytical assessment of tether dynamics is conducted, supported by experimental validation in a controlled test basin, where precise measurements about underwater tether behavior were collected. Directions for further research and system optimization are also discussed.
URL PDF BibTeX

@phdthesis{khanmeh2026taskbased,
	title = "Task-Based Motion Control of an Autonomous Surface Vehicle in a Combined System with a Remotely Operated Vehicle (ASV--ROV)",
	author = "Khanmeh, Juri",
	school = "University of Genova",
	year = 2026,
	type = "Ph.D. Thesis",
	url = "https://hdl.handle.net/11567/1285016",
	note = "PhD Program in Robotics and Intelligent Machines, 38 cycle. Supervisors: Giovanni Indiveri and Enrico Simetti. Head of PhD Program: Antonio Sgorbissa",
	abstract = "Marine robotics plays a crucial role in carrying out a wide range of complex underwater missions. In this context, tethered Remotely Operated Vehicles (ROVs) provide several advantages, including efficient data transmission and a reliable physical connection that ensures safety in emergency situations. However, their operational range is inherently limited by the length of the tether. This study investigates the possibility of extending the operational range of ROVs by introducing a novel control strategy that enables cooperative operation with an Autonomous Surface Vehicle (ASV). The proposed ASV–ROV system addresses two primary challenges: the restricted mobility of the ROV and the potential risk of cable entanglement. To mitigate these issues, a new control framework is developed to ensure smooth ROV motion while minimizing conditions that could lead to tether entanglement. The control system allows the ASV to maintain alignment with the ROV and preserve a desired distance, while simultaneously regulating the length of cable deployed in the water. This thesis presents the control design of the ASV motion for a cooperative navigation with the ROV. The work includes the formulation of a novel control strategy that enables the ASV to autonomously track and follow the ROV while avoiding obstacles and adjusting its trajectory to maintain safe and efficient cooperation. The proposed control framework is validated through comprehensive software-in-the-loop simulations that represents offshore wind farm environments. The numerical results demonstrate the effectiveness and robustness of the system in improving cooperative navigation performance, reducing power consumption, and enhancing operational resilience under dynamic marine conditions. Furthermore, the work of this thesis investigates the impact of tether management on the overall stability and energy efficiency of the ASV–ROV system. An analytical assessment of tether dynamics is conducted, supported by experimental validation in a controlled test basin, where precise measurements about underwater tether behavior were collected. Directions for further research and system optimization are also discussed.",
	pdf = "https://graal.dibris.unige.it/files/phd_theses/2026_Juri_Khanmeh_PhdThesis.pdf"
}

Andrea Tiranti. A distributed autonomous passive sonar system.
Ph.D. Thesis, Università degli Studi di Genova, Genova, Italy, 2025.
Abstract Monitoring marine areas has become a fundamental activity for addressing key challenges such as biodiversity research and conservation, civilian operations on infrastructures and Marine Protected Areas (MPA), and military surveillance, with a particular focus on Anti-Submarine Warfare (ASW) and the protection of critical infrastructures. A current open problem in these scenarios is the tracking of acoustic sources using passive sonar systems. These systems are characterized by silent operation, i.e., without emitting active pulses, and long endurance, making them suitable for continuous and covert monitoring. Detecting and tracking acoustic sources using Passive Acoustic Monitoring (PAM) sensors is a challenging task that requires deploying many sensors to ensure observability of the acoustic source of interest, significantly increasing the cost and effort of maintenance. To overcome these limitations, this thesis investigates the use of Autonomous Underwater Vehicles (AUVs) to build an Underwater Mobile Sensors Network (UWMSN), where the AUVs act as mobile nodes of a distributed, autonomous passive sonar system. The integration of AUVs introduces new challenges, particularly due to the reliance on underwater acoustic communication, which is subject to latencies, low bandwidth, and packet loss. This work addresses these issues by designing distributed control strategies that allow a team of AUVs to track underwater acoustic targets cooperatively. Because the motion of the sensors directly impacts the performance of the tracking algorithm, a cooperative motion planning strategy based on a Partially Observable Markov Decision Process (POMDP) is proposed. To handle the associated computational complexity, a Model Predictive Control (MPC) scheme is used, enabling online optimization over a moving time horizon. A sequential multi-agent decision-making framework ensures that planning remains fully distributed, avoiding the need for a centralized coordinating node and eliminating single points of failure. The proposed strategy is validated through extensive simulations of complex acoustic monitoring scenarios and supported by a real-world proof of concept. Results demonstrate the effectiveness and robustness of the system in improving tracking performance, reducing system costs, and ensuring resilience against communication constraints, AUV failures, and environmental variability.
URL PDF BibTeX

@phdthesis{tiranti2025distributed,
	title = "A distributed autonomous passive sonar system",
	author = "Tiranti, Andrea",
	year = 2025,
	school = "Universit\`a degli Studi di Genova",
	address = "Genova, Italy",
	language = "English",
	type = "Ph.D. Thesis",
	url = "https://hdl.handle.net/20.500.14242/217996",
	note = "URN:NBN:IT:UNIGE-217996",
	abstract = "Monitoring marine areas has become a fundamental activity for addressing key challenges such as biodiversity research and conservation, civilian operations on infrastructures and Marine Protected Areas (MPA), and military surveillance, with a particular focus on Anti-Submarine Warfare (ASW) and the protection of critical infrastructures. A current open problem in these scenarios is the tracking of acoustic sources using passive sonar systems. These systems are characterized by silent operation, i.e., without emitting active pulses, and long endurance, making them suitable for continuous and covert monitoring. Detecting and tracking acoustic sources using Passive Acoustic Monitoring (PAM) sensors is a challenging task that requires deploying many sensors to ensure observability of the acoustic source of interest, significantly increasing the cost and effort of maintenance. To overcome these limitations, this thesis investigates the use of Autonomous Underwater Vehicles (AUVs) to build an Underwater Mobile Sensors Network (UWMSN), where the AUVs act as mobile nodes of a distributed, autonomous passive sonar system. The integration of AUVs introduces new challenges, particularly due to the reliance on underwater acoustic communication, which is subject to latencies, low bandwidth, and packet loss. This work addresses these issues by designing distributed control strategies that allow a team of AUVs to track underwater acoustic targets cooperatively. Because the motion of the sensors directly impacts the performance of the tracking algorithm, a cooperative motion planning strategy based on a Partially Observable Markov Decision Process (POMDP) is proposed. To handle the associated computational complexity, a Model Predictive Control (MPC) scheme is used, enabling online optimization over a moving time horizon. A sequential multi-agent decision-making framework ensures that planning remains fully distributed, avoiding the need for a centralized coordinating node and eliminating single points of failure. The proposed strategy is validated through extensive simulations of complex acoustic monitoring scenarios and supported by a real-world proof of concept. Results demonstrate the effectiveness and robustness of the system in improving tracking performance, reducing system costs, and ensuring resilience against communication constraints, AUV failures, and environmental variability.",
	pdf = "https://graal.dibris.unige.it/files/phd_theses/2025_PhDThesis_A.Tiranti.pdf"
}

Cris Thomas. A Unified Task Priority Control Framework Design for Autonomous Underwater Vehicles.
PhD Thesis, Università degli Studi di Genova, Genova, Italy, 2022.
Abstract In this thesis, we investigate the problem of bringing various behaviours of Autonomous Underwater Vehicles under a common control framework. Thereby, we propose a unified guidance and control framework for AUVs based on the task priority control approach. This incorporate various behaviors such as path following, terrain following, obstacle avoidance, as well as homing and docking to stationary and moving docking stations. The integration of homing and docking maneuvers into the task priority framework is thus a novel contribution of this thesis. This integration allows, for example, to execute homing maneuvers close to uneven seafloor or obstacles, ensuring the safety of the AUV by giving the highest priority to the safety tasks. Furthermore, the proposed approach tackles a wide range of scenarios without ad hoc solutions. Indeed, the proposed approach is well suited for both the emerging trend of resident AUVs, which stay underwater for a long period inside garage stations, exiting to perform inspection and maintenance missions and homing back to them, and for AUVs that are required to dock to moving stations such as surface vehicles, or towed docking stations. The proposed techniques are further studied in a simulation setting, taking into account the rich number of aforementioned scenarios.
URL PDF BibTeX

@phdthesis{cris2022unified,
	title = "A Unified Task Priority Control Framework Design for Autonomous Underwater Vehicles",
	author = "Thomas, Cris",
	year = 2022,
	school = "Universit\`a degli Studi di Genova",
	address = "Genova, Italy",
	type = "PhD Thesis",
	abstract = "In this thesis, we investigate the problem of bringing various behaviours of Autonomous Underwater Vehicles under a common control framework. Thereby, we propose a unified guidance and control framework for AUVs based on the task priority control approach. This incorporate various behaviors such as path following, terrain following, obstacle avoidance, as well as homing and docking to stationary and moving docking stations. The integration of homing and docking maneuvers into the task priority framework is thus a novel contribution of this thesis. This integration allows, for example, to execute homing maneuvers close to uneven seafloor or obstacles, ensuring the safety of the AUV by giving the highest priority to the safety tasks. Furthermore, the proposed approach tackles a wide range of scenarios without ad hoc solutions. Indeed, the proposed approach is well suited for both the emerging trend of resident AUVs, which stay underwater for a long period inside garage stations, exiting to perform inspection and maintenance missions and homing back to them, and for AUVs that are required to dock to moving stations such as surface vehicles, or towed docking stations. The proposed techniques are further studied in a simulation setting, taking into account the rich number of aforementioned scenarios.",
	url = "https://hdl.handle.net/11567/1079804",
	note = "PhD Program in Robotics and Intelligent Machines, 34 cycle. Supervisors: Giuseppe Casalino and Enrico Simetti. Head of PhD Program: Giorgio Cannata",
	pdf = "https://graal.dibris.unige.it/files/phd_theses/2022_PhD_Cris_Thomas_Thesis.pdf"
}

Kourosh Darvish. A Hierarchical Architecture for Flexible Human-Robot Collaboration.
PhD thesis, Università degli Studi di Genova, Genova, Italy, 2019.
Abstract This thesis is devoted to the design of a software architecture for Human-Robot Collaboration (HRC), enhancing robots' abilities to work alongside humans. It proposes FlexHRC, a hierarchical and flexible human-robot cooperation architecture designed to provide collaborative robots with extended autonomy in tasks with high variability, introducing techniques at perception, representation, and action levels for effective collaborative performance.
URL PDF BibTeX

@phdthesis{darvish2019hierarchical,
	title = "A Hierarchical Architecture for Flexible Human-Robot Collaboration",
	author = "Darvish, Kourosh",
	year = 2019,
	school = "Universit\`a degli Studi di Genova",
	address = "Genova, Italy",
	type = "PhD thesis",
	abstract = "This thesis is devoted to the design of a software architecture for Human-Robot Collaboration (HRC), enhancing robots' abilities to work alongside humans. It proposes FlexHRC, a hierarchical and flexible human-robot cooperation architecture designed to provide collaborative robots with extended autonomy in tasks with high variability, introducing techniques at perception, representation, and action levels for effective collaborative performance.",
	url = "https://hdl.handle.net/20.500.14242/63500",
	note = "URN:NBN:IT:UNIGE-63500; Robotics and Autonomous Systems (Bioengineering and Robotics), 31 cycle. Supervisors: Giuseppe Casalino, Enrico Simetti and Fulvio Mastrogiovanni.",
	pdf = "https://graal.dibris.unige.it/files/phd_theses/2019_PhDThesis_K.Darvish.pdf"
}

Francesco Wanderlingh. Cooperative Robotic Manipulation for the Smart Factory.
Ph.D. Thesis, University of Genova, Genova, Italy, 2018.
Abstract To tackle the upcoming needs of the new Industry 4.0 paradigm, where cyberphysical systems communicate and cooperate with each other and humans in real time, the control of a robot must be able to guarantee a high level of flexibility, in order to accomplish a variety of tasks that go beyond the usual, standardized, robotic cell ones taking place within a very structured environment. Stemming from the wellestablished line of research on control of high degrees of freedom marine systems investigated in the GRAAL Lab where I carried out my PhD, the focus of this work has been to develop a general robot control framework to transfer the know-how acquired in years of marine research to industrial scenarios. In the perspective of building a solution that fits them all, removing the need to create specific solutions for every single problem, the main idea has been to develop a framework that provides a set of basic control capabilities, as building blocks for the robots to perform complex actions. In this context the PhD work focused on the development of a real time control framework and adaptation of the involved structures, to develop an experimentally working set up that is capable of: handling different robotic structures (fixed base arms, single and dual arm mobile manipulators either working on ground or underwater) in a uniform way; handling cooperation between different agents; being able to perform interaction tasks with the environment and human beings; exposing interfaces to guarantee a good integration with the higher levels of planning, decision and command, with the goal of releasing them from dealing with lower level control problems. From the technological point of view, a key objective has been to develop the software architecture, implementing the control framework, in order to achieve the highest possible re-usability and flexibility. This allowed an easy application of the control framework to different robotic setups, minimizing the development effort to adapt not only the control laws, but also all the collateral supporting software needed to interact with the specific robot-software environment. To the above aims I exploited different hardware resources such as two YouBots platforms and a Baxter bi-manual robotic system, collecting experimental results which validate the proposed approach.
URL PDF BibTeX

@phdthesis{wanderlingh2018cooperative,
	title = "Cooperative Robotic Manipulation for the Smart Factory",
	author = "Wanderlingh, Francesco",
	year = 2018,
	school = "University of Genova",
	address = "Genova, Italy",
	type = "Ph.D. Thesis",
	abstract = "To tackle the upcoming needs of the new Industry 4.0 paradigm, where cyberphysical systems communicate and cooperate with each other and humans in real time, the control of a robot must be able to guarantee a high level of flexibility, in order to accomplish a variety of tasks that go beyond the usual, standardized, robotic cell ones taking place within a very structured environment. Stemming from the wellestablished line of research on control of high degrees of freedom marine systems investigated in the GRAAL Lab where I carried out my PhD, the focus of this work has been to develop a general robot control framework to transfer the know-how acquired in years of marine research to industrial scenarios. In the perspective of building a solution that fits them all, removing the need to create specific solutions for every single problem, the main idea has been to develop a framework that provides a set of basic control capabilities, as building blocks for the robots to perform complex actions. In this context the PhD work focused on the development of a real time control framework and adaptation of the involved structures, to develop an experimentally working set up that is capable of: handling different robotic structures (fixed base arms, single and dual arm mobile manipulators either working on ground or underwater) in a uniform way; handling cooperation between different agents; being able to perform interaction tasks with the environment and human beings; exposing interfaces to guarantee a good integration with the higher levels of planning, decision and command, with the goal of releasing them from dealing with lower level control problems. From the technological point of view, a key objective has been to develop the software architecture, implementing the control framework, in order to achieve the highest possible re-usability and flexibility. This allowed an easy application of the control framework to different robotic setups, minimizing the development effort to adapt not only the control laws, but also all the collateral supporting software needed to interact with the specific robot-software environment. To the above aims I exploited different hardware resources such as two YouBots platforms and a Baxter bi-manual robotic system, collecting experimental results which validate the proposed approach.",
	url = "https://hdl.handle.net/11567/1159996",
	note = "PhD Program in Robotics and Intelligent Machines, 30 cycle. Supervisors: Pino Casalino and Enrico Simetti. Head of PhD Program: Paolo Massobrio",
	pdf = "https://graal.dibris.unige.it/files/phd_theses/2018_PhD_F.%20Wanderlingh_Thesis.pdf"
}

Enrico Simetti. Planning and control of autonomous marine systems.
PhD Thesis, Università degli Studi di Genova, Genova, Italy, 2013.
Abstract This thesis investigates planning and control strategies for autonomous marine systems, focusing on approaches that enable robust navigation and operational autonomy in marine environments.
URL PDF BibTeX

@phdthesis{simetti2013planning,
	title = "Planning and control of autonomous marine systems",
	author = "Simetti, Enrico",
	year = 2013,
	school = "Universit\`a degli Studi di Genova",
	address = "Genova, Italy",
	type = "PhD Thesis",
	url = "https://hdl.handle.net/20.500.14242/344498",
	note = "URN:NBN:IT:BNCF-344498",
	abstract = "This thesis investigates planning and control strategies for autonomous marine systems, focusing on approaches that enable robust navigation and operational autonomy in marine environments.",
	pdf = "files/phd_theses/2012_E.Simettic_phd.pdf"
}

Alessio Turetta. Self-Coordinating Distributed Control Algorithms for Multi-Robot Systems.
University of Genova, Genova, Italy, 2005.
Abstract This thesis presents a modular and computationally distributed control architecture for Multi-Robot Systems (MRS), defined as temporary compositions of independently controlled robotic subsystems cooperating to execute common tasks. The research aims at preserving local control functionalities while avoiding centralized coordinators. Three coordination strategies are analyzed: a centralized method and two decentralized distributed approaches. The decentralized techniques rely on self-coordination principles and local information exchange, including an iterative pipelined scheme and a dynamic-programming-based distributed LQ control formulation. Convergence properties and simulation results demonstrate effectiveness and scalability. The proposed framework is particularly suited for modular robotic systems, and its application to the P2MR (Plug’n’Play Modular Robot) platform under development at DIST is discussed.
URL PDF BibTeX

@phdthesis{Turetta2005,
	author = "Alessio Turetta",
	title = "Self-Coordinating Distributed Control Algorithms for Multi-Robot Systems",
	school = "University of Genova",
	year = 2005,
	month = "",
	address = "Genova, Italy",
	note = "Ph.D. Thesis in Robotics (XVII Cycle)",
	abstract = "This thesis presents a modular and computationally distributed control architecture for Multi-Robot Systems (MRS), defined as temporary compositions of independently controlled robotic subsystems cooperating to execute common tasks. The research aims at preserving local control functionalities while avoiding centralized coordinators. Three coordination strategies are analyzed: a centralized method and two decentralized distributed approaches. The decentralized techniques rely on self-coordination principles and local information exchange, including an iterative pipelined scheme and a dynamic-programming-based distributed LQ control formulation. Convergence properties and simulation results demonstrate effectiveness and scalability. The proposed framework is particularly suited for modular robotic systems, and its application to the P2MR (Plug’n’Play Modular Robot) platform under development at DIST is discussed.",
	url = "https://hdl.handle.net/20.500.14242/230247",
	pdf = "https://graal.dibris.unige.it/files/phd_theses/Turetta_PhD_thesis.pdf"
}

Giovanni Indiveri. Modelling and Identification of Underwater Robotic Systems.
University of Genova, Genova, Italy, 1998.
Abstract This thesis addresses modelling and identification issues for underwater robotic systems, with particular reference to ROVs. A two-step identification procedure based on on-board sensors is proposed: drag coefficients are first estimated via constant-speed tests, and inertia parameters are subsequently identified using designed sinusoidal thrust inputs. Experimental validation on the ROMEO ROV demonstrates the feasibility of low-cost identification and highlights the relevance of propeller–propeller and propeller–hull interactions. Parameter variances confirm the effectiveness of the approach. The work also investigates planar motion control of nonholonomic vehicles and proposes a globally asymptotically convergent smooth feedback law for point stabilization of car-like robots, with bounded curvature and guaranteed convergence even under actuator saturation. Applications to underwater vehicles and minimum-curvature path planning are discussed.
URL PDF BibTeX

@phdthesis{Indiveri1998,
	author = "Giovanni Indiveri",
	title = "Modelling and Identification of Underwater Robotic Systems",
	school = "University of Genova",
	year = 1998,
	month = "",
	address = "Genova, Italy",
	note = "Ph.D. Thesis in Electronic Engineering and Computer Science",
	abstract = "This thesis addresses modelling and identification issues for underwater robotic systems, with particular reference to ROVs. A two-step identification procedure based on on-board sensors is proposed: drag coefficients are first estimated via constant-speed tests, and inertia parameters are subsequently identified using designed sinusoidal thrust inputs. Experimental validation on the ROMEO ROV demonstrates the feasibility of low-cost identification and highlights the relevance of propeller–propeller and propeller–hull interactions. Parameter variances confirm the effectiveness of the approach. The work also investigates planar motion control of nonholonomic vehicles and proposes a globally asymptotically convergent smooth feedback law for point stabilization of car-like robots, with bounded curvature and guaranteed convergence even under actuator saturation. Applications to underwater vehicles and minimum-curvature path planning are discussed.",
	url = "https://hdl.handle.net/20.500.14242/252329",
	pdf = "https://graal.dibris.unige.it/files/phd_theses/Indiveri.PhD.98.COMPLETE.pdf"
}