In order to obtain a pass in this subject, a minimum score of 50 must be passed 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. 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 early sitting (December): students who opt for this sitting will have to repeat the tutored work and oral presentation methodologies. It is necessary to contact the lecturers at the beginning of the term in order to establish appropriate deadlines.

Students enrolled part-time, in the event of not being able to make the oral presentation with the rest of the students nor in person neither online, an alternative date must be arranged with the teachers. This modification must be requested to the teachers of the subject at the beginning of the course.

The fraudulent realisation of tests or activities, once verified, will directly imply the qualification of failing "0" in the subject in the corresponding call, thus invalidating any qualification obtained in all the assessment activities for the extraordinary call.

Learning outcomes	Study programme competences
Ability to design, simulate and/or implement technological solutions involving the use of autonomous mobile robots in an industrial environment.	AC1 AC4	BC2 BC5 BC9 BC10 BC14	CC1 CC3
Understanding the scope and limitations of current autonomous mobile robots in terms of their sensing and actuation capabilities.	AC1 AC4	BC9 BC14	CC1 CC3
Understanding the fundamentals and main control techniques in autonomous robotics, and implement them practically on a mobile robot.	AC1 AC4	BC9 BC14	CC1 CC3
Understanding the particularities of using computer vision techniques in mobile robotics.	AC1 AC4	BC9 BC14	CC1 CC3
Understanding the fundamentals of the main problems of mobile autonomous robotics: localization, mapping and path planning, as well as a practical implementation of some of the main existing techniques.	AC1 AC4	BC9 BC14	CC1 CC3

Topic	Sub-topic
Introduction to mobile robotics	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	- Graph search - Wavefront-based planning

Methodologies / tests	Competencies	Ordinary class hours	Student’s personal work hours	Total hours
Guest lecture / keynote speech	B5 B9 C1 C3	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.	30

Assessment comments
In order to obtain a pass in this subject, a minimum score of 50 must be passed 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. 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 early sitting (December): students who opt for this sitting will have to repeat the tutored work and oral presentation methodologies. It is necessary to contact the lecturers at the beginning of the term in order to establish appropriate deadlines. Students enrolled part-time, in the event of not being able to make the oral presentation with the rest of the students nor in person neither online, an alternative date must be arranged with the teachers. This modification must be requested to the teachers of the subject at the beginning of the course. The fraudulent realisation of tests or activities, once verified, will directly imply the qualification of failing "0" in the subject in the corresponding call, thus invalidating any qualification obtained in all the assessment activities for the extraordinary call.

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

Other comments
The documents to be deliver in this subject: - Virtual format or digital support will be requested. - They'll be done on the Virtual Campus without printing them. In case they’re done in paper: - Don't use plastics. - Use double-sided printing. - Use recycled paper. - Avoid printing drafts.