In order to obtain a pass in this subject, a minimum mark of 50 must be obtained in all the above methodologies, with a minimum mark of 35 in the Tutored Work and 15 in the Oral Presentation.

If the student does not pass the subject at the first sitting, he/she will have to repeat the necessary activities of the methodology/s that were not passed at the second sitting. As an example, if a student passed the Oral Presentation part but failed the Supervised Assignments, he/she will have to repeat the practical assignments necessary to achieve a pass, normally those that were not passed individually.

Assessment of the extraordinary call: students who opt for this call will have to carry out the tutored work and oral presentation methodologies. Students must contact their teachers at the beginning of the term (January) in order to have enough time to submit their work.

Students enrolled on a part-time basis must carry out the tutored work and oral presentation methodologies. In case of not being able to do the oral presentation with the rest of the students, they will have to arrange an alternative date with the professors in all the sessions. It is necessary to contact the lecturers at the beginning of the term (January) in order to have a sufficient deadline.

In the case of plagiarism in internships or teaching assignments, article 11, section 4 b) of the UDC Student Disciplinary Regulations will be taken into account:

b) Failure grade in the exam session in which the offence is committed and with respect to the subject in which it is committed: the student will be graded with a "fail" (numerical grade 0) in the corresponding exam session of the academic year, whether the offence is committed on the first or second occasion. To this end, the student's grade will be modified at the first opportunity, if necessary.

Learning outcomes	Study programme competences
Knowledge of the particularities of mobile robots in the context of industrial robotics, and in particular of autonomous mobile robots.	AC1 AC4	BC2 BC5 BC9 BC10 BC14	CC1 CC3
Knowledge of the physical principles of sensors used in autonomous robot navigation, and their application contexts.	AC1 AC4	BC9 BC14	CC1 CC3
Knowledge of the problems and main solutions in trajectory planning and autonomous navigation.	AC1 AC4	BC9 BC14	CC1 CC3
Knowledge of the main static and dynamic modelling techniques of the environment in which robots move.	AC1 AC4	BC9 BC14	CC1 CC3
Knowledge of the problems and the main existing solutions in localisation and mapping.	AC1 AC4	BC9 BC14	CC1 CC3

Topic	Sub-topic
Introduction to mobile robotics	Kinematics of mobile robots Locomotion: - Motors - Degrees of freedom - Legs - Wheels - Other effectors
Perception in mobile robotics	- Types of sensors - Sensors in mobile robotics -- Contact -- Distance -- Computer vision -- IMU -- GPS - Control architectures -- Deliberative -- Reactive -- Hybrid -- Communications
Movement control	- Position control system
Localization and mapping	- Navigation: -- Topological -- Metric - Simultaneous localisation and mapping -- Localisation (odometry, beacons) -- Visual SLAM
Trajectory planning and navigation	- Graph search - Wavefront-based planning

Methodologies / tests	Competencies	Ordinary class hours	Student’s personal work hours	Total hours
Guest lecture / keynote speech	B5 B9 C3 C1	10.5	4.5	15
ICT practicals	B2 B5 B9 B10 B14 C1 C3	10	10	20
Oral presentation	A1 A4 B9 B10 B14	0.5	6.5	7
Supervised projects	A1 A4 B2 B10 B14 C1 C3	0	30	30

Personalized attention		3	0	3

(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies	Description
Guest lecture / keynote speech	Oral presentation of the theoretical syllabus by the teachers of the course.
ICT practicals	Face-to-face sessions with the computer in which teachers will explain the use and programming of the mobile robotics techniques seen in theory, so that students acquire sufficient skills to use them autonomously. Real and/or simulated robots will be used.
Oral presentation	Theory paper(s) on a topic proposed by the teachers of the course, which must be presented in front of classmates and also handed in in writing.
Supervised projects	Carrying out work/projects outside the classroom in which different programmes related to the topics seen in practical classes will be implemented through ICT, using real or simulated robots selected by the subject teachers. These projects will be carried out autonomously by the students and their progress will be supervised by the lecturers.

Methodologies	Competencies	Description	Qualification
Supervised projects	A1 A4 B2 B10 B14 C1 C3	Several practical tasks will be proposed throughout the course focused on solving mobile robotics 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 lecturers.	70
Oral presentation	A1 A4 B9 B10 B14	The oral presentation of the theoretical work/works, the written version of the same and the active participation in the presentations of the classmates have an important weight in the final grade of the course.	20
Guest lecture / keynote speech	B5 B9 C3 C1	During the lectures, in person activities will be carried out to reinforce the comprehension of the theoretical aspects.	10

Assessment comments
In order to obtain a pass in this subject, a minimum mark of 50 must be obtained in all the above methodologies, with a minimum mark of 35 in the Tutored Work and 15 in the Oral Presentation. If the student does not pass the subject at the first sitting, he/she will have to repeat the necessary activities of the methodology/s that were not passed at the second sitting. As an example, if a student passed the Oral Presentation part but failed the Supervised Assignments, he/she will have to repeat the practical assignments necessary to achieve a pass, normally those that were not passed individually. Assessment of the extraordinary call: students who opt for this call will have to carry out the tutored work and oral presentation methodologies. Students must contact their teachers at the beginning of the term (January) in order to have enough time to submit their work. Students enrolled on a part-time basis must carry out the tutored work and oral presentation methodologies. In case of not being able to do the oral presentation with the rest of the students, they will have to arrange an alternative date with the professors in all the sessions. It is necessary to contact the lecturers at the beginning of the term (January) in order to have a sufficient deadline. In the case of plagiarism in internships or teaching assignments, article 11, section 4 b) of the UDC Student Disciplinary Regulations will be taken into account: b) Failure grade in the exam session in which the offence is committed and with respect to the subject in which it is committed: the student will be graded with a "fail" (numerical grade 0) in the corresponding exam session of the academic year, whether the offence is committed on the first or second occasion. To this end, the student's grade will be modified at the first opportunity, if necessary.

Basic	• Siegwart, Roland (2004). Introduction to autonomous mobile robots. MIT Press Nehmzow, Ulrich (2003). Mobile robotics a practical introduction. Springer Kelly, Alonzo (2013). Mobile robotics: mathematics, models and methods. Cambridge University Press

Complementary	Robin R. Murphy (2000). Introduction to AI Robotics. A Bradford Book 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 Lynch, Kevin (2017). Modern robotics : mechanics, planning, and control. Cambridge University Press