| Study programme competencies |
| Code | Study programme competences |
| A4 | CE4 – Demonstrate knowledge, understanding and competences in the field of design and operation of robots and marine autonomous vehicles (RAS). |
| B2 | CB6 - Acquire and understand knowledge that provides a basis or opportunity to be original in the development and / or application of ideas, usually in a research context. |
| B3 | CB7 - That students know how to apply the acquired knowledge and their ability to solve problems in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their area of study. |
| B4 | CB8 - That students are able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgments. |
| B5 | CB9 – That students are able to communicate their conclusions -and the knowledge and ultimate reasons that sustain them- to specialized and non-specialized publics in a clear and unambiguous way. |
| B6 | CB10 - That students have the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous. |
| B7 | CG1 – To display the adequate intercultural competence to successfully navigating within multicultural learning environments and to implement basic management principles suitable for a multicultural working environment. |
| B8 | CG2 – To express an attitude of intellectual inquisitiveness and open-mindedness. |
| B9 | CG3 – To have the capability to use knowledge, skills, ideas, theory, and modern engineering concepts to create new or significantly improved real engineering applications. |
| B11 | CG5 – To have the capability to identify, formulate and solve engineering problems within realistic constraints. |
| B13 | CG7 – To have the capability to critically analyse, synthesise, interpret and summarise complex scientific processes. |
| C2 | CT2 - Mastering oral and written expression in a foreign language. |
| C3 | CT3 - Using ICT in working contexts and lifelong learning. |
| C4 | CT4 - Acting as a respectful citizen according to democratic cultures and human rights and with a gender perspective. |
| C6 | CT6 - Acquiring skills for healthy lifestyles, and healthy habits and routines. |
| C7 | CT7 -Developing the ability to work in interdisciplinary or transdisciplinary teams in order to offer proposals that can contribute to a sustainable environmental, economic, political and social development. |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| Capacity for applying mathematical and ICT methods and tools to define, design, operate and maintain advanced marine robotic systems and for understanding and developing the needed algorithms and methods. | BC1 BC2 BC3 BC4 BC5 BC6 BC7 BC10 BC12 |
CC2 CC3 CC4 CC6 CC7 |
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| Understanding the difference between autonomous and non-autonomous operation in robotics, and how it fits into the Artificial Intelligence field | AC4 |
BC3 BC5 BC7 BC12 |
CC4 |
| Acquiring the knowledge about sensors and actuators relevant in marine vehicles to provide them with autonomous capabilities | AC4 |
BC1 BC3 BC5 BC7 BC12 |
CC4 CC6 CC7 |
| Understanding the fundamentals of autonomous robotic control, and how classical techniques are very important to achieve a proper response. Being able to apply these concepts in navigation tasks | AC4 |
BC1 BC2 BC3 BC5 BC7 BC12 |
CC3 CC4 CC6 CC7 |
| Capacity for using a marine vehicle simulator and programming it, including all the previous knowledge about sensors, actuators and autonomous/classical control | AC4 |
BC2 BC3 BC5 BC6 BC7 BC8 BC10 BC12 |
CC3 CC6 CC7 |
| Contents |
| Topic | Sub-topic |
| Topic 1. Introduction to autonomous vehicles | - Artificial Intelligence - Autonomous robots - Autonomous vehicles |
| Topic 2. Sensors and actuators in marine vehicles | - Sensors: -- Sound based (Sonar, DVL, range finders...) -- Vision and laser based (Cameras, LIDAR...) -- Inertial Measurement Units (IMU) -- GNSS and alternative positioning systems - Actuators: -- Thrusters and alternative propulsion methods -- Arms and grippers |
| Topic 3. Autonomous control | - Open loop control - Closed loop control - PID - Intelligent architectures -- Reactive -- Deliberative -- Hybrid |
| Topic 4. Autonomous navigation | - Localization - Mapping - Path planning |
| Topic 5. Programming underwater vehicles | - Gazebo simulation model - Programming framework - Real underwater vehicle |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| ICT practicals | B3 B6 B8 C6 C3 | 18 | 18 | 36 |
| Guest lecture / keynote speech | B2 B4 B6 C4 C6 | 18 | 9 | 27 |
| Supervised projects | A4 B3 B4 B5 B6 B7 B8 B9 B11 B13 C2 C3 C7 | 0 | 55 | 55 |
| Field trip | A4 B3 B7 B9 B11 B13 C7 C4 | 4 | 8 | 12 |
| Mixed objective/subjective test | A4 B4 B5 B6 B11 B13 C2 | 2 | 16 | 18 |
| Personalized attention | 2 | 0 | 2 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| ICT practicals | Practical classes carried out in the ICT lab, with the objective of learning how to program an autonomous marine vehicle (real or simulated) to develop a simple mission. In these classes, the teacher will help students to properly understand the topics |
| Guest lecture / keynote speech | Masterclass where teachers explain the theoretical concepts of the topics, and students can ask questions. |
| Supervised projects | Autonomous work where students must solve some challenge involving programming an autonomous marine vehicle to solve a task. There can be one of incremental complexity or more than one with independent objectives. In this methodology, students will be organised in groups, so they will have to collaborate to achieve the goal. |
| Field trip | A field trip will be made to the UDC ship model basin to collect data on navigation tests of autonomous marine vehicles. |
| Mixed objective/subjective test | Written or oral examination where students will show their understanding of the theoretical concepts of the subject. |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies | Description | Qualification |
| Mixed objective/subjective test | A4 B4 B5 B6 B11 B13 C2 | Students will have to show their knowledge and understanding of the theoretical concepts of the subject by means of a written or oral activity | 30 |
| Supervised projects | A4 B3 B4 B5 B6 B7 B8 B9 B11 B13 C2 C3 C7 | One or more projects will be proposed throughout the course focused on solving realistic problems with autonomous marine problems using real or simulated robots. These tasks will be developed autonomously by the student outside the classroom and must be defended in front of the teachers. | 60 |
| Field trip | A4 B3 B7 B9 B11 B13 C7 C4 | The correct preparation, execution and understanding of the field trip will be assessed by the teachers of the subject. Students must prepare a report which will be evaluated. | 10 |
| Assessment comments | |||
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In order to pass this subject, a minimum score of 50 must be obtained by adding all the above methodologies, there being no minimum in any of them. If the student does not pass the subject in the ordinary exam, he/she will have to repeat the necessary activities of the methodology/s that were not passed in the extraordinary exam. General EMJMD Sustainable Ship and Shipping SEAS 4.0 evaluation rules: - Students will have only two oportunities to pass a course. If failing to do so, they may be forced to leave the degree. - No part time or lecture attendance exemption are allowed in this degree. |
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| Sources of information |
| Basic |
Geoff Roberts and Robert Sutton (2006). Advances in unmanned marine vehicles. Institution of Engineering and Technology
Thor I. Fossen (2011). Handbook of Marine Craft Hydrodynamics and Motion Control. John Wiley & Sons
Robin R. Murphy (2000). Introduction to AI Robotics. A Bradford Book |
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| Complementary |
Joseph, Lentin (2015). Learning robotics using Python : design, simulate, program, and prototype an interactive autonomous mobile robot from scratch with the help of Python, ROS, and Open-CV. Packt Publishing |
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| Recommendations | ||
| Subjects that it is recommended to have taken before | ||
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| Subjects that are recommended to be taken simultaneously | ||
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| Subjects that continue the syllabus |
| Other comments | |
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To help in achieving a sustainable environment and to get the objective of number 5 action of the "Ferrol Green Campus Action Plan" (Healthy and environmentaly and socially sustainable research and teaching): The assignments to be done in this course: - Will be required in digital format. - Will be delivered using Moodle, with no need to print them. In case it is necessary to print them: - Plastics won´t be used. - Two side printing will be used. - Recycled paper will be used. - Printing drafts will be avoided. A sustainable use of the resources should be done, together with the prevention of negative impacts on the environment. |