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Orbital Robotics and Distributed Space Systems

01DWGMT

A.A. 2022/23

Course Language

Inglese

Degree programme(s)

Master of science-level of the Bologna process in Ingegneria Aerospaziale - Torino

Course structure
Teaching Hours
Lezioni 45
Esercitazioni in aula 15
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Romano Marcello   Professore Ordinario ING-IND/05 45 6 0 0 2
Co-lectuers
Espandi

Context
SSD CFU Activities Area context
ING-IND/05 6 B - Caratterizzanti Ingegneria aerospaziale ed astronautica
2022/23
Orbital robotics systems, that are covered in the first part of this course, are artificial satellite systems that can physically interact with another orbiting object by using actively controlled on board mechanisms that enable grasping, manipulation and mobility: a paradigmatic example is an artificial satellite equipped with an onboard robotic manipulator. Applications of orbital robotics systems include On-orbit Servicing, Assembly and Manufacturing, and space debris removal. Distributed Space Systems, that are covered in the second part of this course, are artificial satellite systems that occupy a region considerably larger than the one pertaining to a single traditional artificial satellite. Examples of Distributed Space Systems are Formation Flying Satellites, Tethered Satellites and Very Large Satellite Systems. Applications of Distributed Space Systems include: high-resolution Earth or astronomic observation, and collection and retransmission of solar power. This course will transfer knowledge of analytical methods and formulation practices for developing mathematical models of motion for classes of Orbital Robotics and Distributed Space Systems, under the effect of both environmental actions as well as actions by on-board actuators, such as thrusters and momentum exchange devices. Furthermore, the course will build comprehension of how these mathematical models of motion are used for the synthesis of autonomous guidance, navigation and control algorithms that enable the execution of translational, rotational and reconfiguration maneuvers to achieve specific mission capabilities. Finally, the course will develop comprehension on how software libraries are coded and used to perform numerical simulations to study the physical phenomenon of motion in specific instances of Orbital Robotics and Distributed Space Systems, and to assess the performance of selected guidance, navigation and control logics during specific maneuver scenarios. Examples will be considered of space systems encompassing current and emerging space technology solutions, and of maneuver scenarios pertaining to real space missions, either previously flown or planned.
Orbital Robotics and Distributed Space Systems will enable new, emerging and future, space mission capabilities for applications with a broad societal impact such as: -high accuracy, large field, low Earth observation and remote sensing, to provide geographical data required by new services in the framework of the new space economy and needed to support climate-change adaptation and mitigation plans and; -high resolution astronomical observation, needed to study extra-solar planet systems and search for extra-terrestrial life signatures; -space based solar power collection and retransmission; -sustainability of the space environment, e.g., space-debris removal to mitigate the occurrence of Kessler syndrome, or in the context of servicing and reuse, situational awareness, space surveillance and security, and space logistics. 

Orbital robotics systems, that are covered in the first part of this course, are artificial satellite systems that can physically interact with another orbiting object by using actively controlled on board mechanisms that enable grasping, manipulation and mobility: a paradigmatic example is an artificial satellite equipped with an onboard robotic manipulator. Highlighted applications of orbital robotics systems include On-orbit Servicing, Assembly and Manufacturing, and space debris removal. 

Distributed Space Systems, that are covered in the second part of this course, are artificial satellite systems that occupy a region considerably larger than the one pertaining to a single traditional artificial satellite while maintaining a co-orbital flight condition with respect to a planetary central body or equilibrium point. Examples of Distributed Space Systems are Formation Flying Satellites, Tethered Satellites and Very Large Satellite Systems (of dimensions of order of magnitude of hundreds of meters to kilometers). Highlighted applications of Distributed Space Systems include: high-resolution Earth or astronomic observation, and collection and retransmission of solar power. 

This course will transfer knowledge of analytical methods and formulation practices for developing mathematical models of motion for classes of Orbital Robotics and Distributed Space Systems, under the effect of both environmental actions as well as actions by on-board actuators, such as thrusters and momentum exchange devices. Furthermore, the course will build comprehension of how these mathematical models of motion are used for the synthesis of autonomous guidance, navigation and control algorithms that enable the execution of translational, rotational and reconfiguration maneuvers to achieve specific mission capabilities. Finally, the course will develop comprehension on how software libraries are coded and used to perform numerical simulations to study the physical phenomenon of motion in specific instances of Orbital Robotics and Distributed Space Systems, and to assess the performance of selected guidance, navigation and control logics during specific maneuver scenarios. Examples will be considered of space systems encompassing current and emerging space technology solutions, and of maneuver scenarios pertaining to real space missions, either previously flown or planned.
At the end of this course the following learning outcomes will be achieved, regarding Orbital Robotics (OR) and Distributed Space Systems (DSS). The student will: -know and comprehend, at a system engineering level, the fundamental elements pertaining to their Mechanics, and Guidance, Navigation & Control aspects; -know and comprehend the classification of several possible architectures; -know and comprehend the mathematical description of kinematics (for the translational, rotational and internal configuration), differential kinematics, and kinetics; -know and comprehend how to model the most common external actions (due to environment and actuators) as well as internal actions (due to internal dynamics and actuators); -know and comprehend selected analytical methods and techniques, based on Newtonian and analytical mechanics, for formulating mathematical models of the dynamics; -be able to apply the acquired methods for writing the equations of motion of specific instances of spacecraft-manipulator systems by leveraging symbolic computation; -know and comprehend selected method for the synthesis of autonomous Guidance, Navigation & Control logics to accomplish selected desire maneuvers; -be able to code prototype software to perform numerical simulation of their natural and forced motion; -be able to validate that software, i.e., to check whether it fulfills its intended purpose; -be able to use that software to preliminarily verify, via numerical simulation experiments, key performances (e.g., the satisfaction of selected requirements regarding guidance and control) by specific instances of OR or DSS systems, during sample maneuver scenarios; -be familiar, at a system engineering level, with the current technology pertaining to Orbital Robotics and Distributed Space Systems; -gain a general engineering intuition in terms of orders of magnitude of quantities involved, system capabilities, limitations, and possible innovative systems and applications.
At the end of this course the following learning outcomes will be achieved, regarding Orbital Robotics (OR) and Distributed Space Systems (DSS). The student will: -know and comprehend, at a system engineering level, the fundamental elements pertaining to their Astrodynamics, and Guidance, Navigation & Control aspects; -know and comprehend the classification of several possible architectures and their applications; -know and comprehend the mathematical description of kinematics (for the translational, rotational and internal configuration), differential kinematics, and kinetics; -know and comprehend how to model the most common external actions (due to environment, in primis gravity, and actuators) as well as internal actions (due to internal dynamics and actuators); -know and comprehend selected analytical methods and techniques, based on Newtonian and analytical mechanics, for formulating mathematical models of the dynamics; -be able to apply the acquired methods for writing the mathematical models of specific instances of Orbital Robotics and Distributed Space systems by leveraging symbolic computation; -know and comprehend selected method for the synthesis of autonomous Guidance, Navigation & Control logics to accomplish selected desire maneuvers; -be able to code prototype software to perform numerical simulation of their natural and forced motion; -be able to validate that software, i.e., to check whether it fulfills its intended purpose; -be able to use that software to preliminarily verify, via numerical simulation experiments, key performances (e.g., the satisfaction of selected requirements regarding guidance and control) by specific instances of OR or DSS systems, during sample maneuver scenarios; -be familiar, at a system engineering level, with the current technology; -be familiar with kino-dynamic laboratory experimentation methods; -gain a general engineering intuition in terms of orders of magnitude of quantities involved, system capabilities, limitations, and possible innovative systems and applications.
Knowledge, at the fundamental levels, of Newtonian mechanics (e.g., from a previous course in classical Physics or/and in engineering mechanics), and control theory (e.g., from a previous course in automatic linear control). Previous experience with software coding, e.g., in Matlab.
Knowledge, at the fundamental levels, of Newtonian mechanics (e.g., from a previous course in classical physics or/and engineering mechanics), and control theory (e.g., from a previous course in automatic linear control). Previous experience with software coding and performing numerical simulations, e.g., in Matlab.
20 hours each for Orbital Robotics Systems and Distributed Space Systems regarding: mathematical modeling of motion, synthesis of guidance, navigation and control methods, system engineering and technology 10 hour each for Orbital Robotics Systems and Distributed Space Systems regarding: coding of prototype simulation software, execution of numerical experiments of validation and verification
19.5 hours each for Orbital Robotics Systems and Distributed Space Systems regarding: mathematical modeling of motion, synthesis of guidance, navigation and control methods, system engineering and technology, illustration and discussions about possible emerging and future applications 10.5 hours each for Orbital Robotics Systems and Distributed Space Systems regarding: coding of prototype simulation software for symbolic and numerical computations, execution of numerical experiments of validation and verification
This course will be taught in English.
This course will be taught in English. Classes will be organized to finish before or around the end of May.
This course will be structured as follows: -39 hours of lecture -21 hours of exercises on a computer
This course will be structured as follows: -39 hours of lecture -21 hours of exercises on a computer
The course reading materials will consist primarily of class notes developed by Prof. Romano, and distributed during the course. Other reference materials (as textbook excerpts and specialized papers) will be indicated during the course.
The course reading materials will consist primarily of class notes developed by the teacher, and distributed during the course. Other reference materials (as textbook excerpts and specialized papers and reports) will be indicated during the course.
ModalitÓ di esame: Prova scritta (in aula); Elaborato progettuale individuale;
Exam: Written test; Individual project;
... The exam is aimed at ascertaining knowledge of the topics listed in the official teaching program and the ability to apply the theory and related calculation methods to solving exercises. The evaluations are expressed out of thirty and the exam is passed if the score reported is at least 18/30.
Gli studenti e le studentesse con disabilitÓ o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'UnitÓ Special Needs, al fine di permettere al/la docente la declinazione pi¨ idonea in riferimento alla specifica tipologia di esame.
Exam: Written test; Individual project;
The exam is aimed at ascertaining knowledge of the topics listed in the official teaching program and the ability to apply the theory and related calculation methods to solving exercises. The evaluations are expressed out of thirty and the exam is passed if the score reported is at least 18/30.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
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