Identifying Data 2019/20
Subject (*) Robotics Code 614G01098
Study programme
Grao en Enxeñaría Informática
Descriptors Cycle Period Year Type Credits
Graduate 2nd four-month period
 Fourth Optional 6
Language
English
Teaching method Face-to-face
Prerequisites
Department Ciencias da Computación e Tecnoloxías da Información
Computación
Coordinador
Santos Reyes, Jose
 E-mail
jose.santos@udc.es
Lecturers
Becerra Permuy, Jose Antonio
Bellas Bouza, Francisco Javier
Santos Reyes, Jose
 E-mail
jose.antonio.becerra.permuy@udc.es
francisco.bellas@udc.es
jose.santos@udc.es
Web
General description Na materia de Robótica estúdanse os principais conceptos de robótica autónoma, facendo énfase no deseño automático de estratexias de control. Para iso, o contido da materia parte das estratexias clásicas de control para chegar ás máis actuais baseadas en conceptos da intelixencia computacional, tales como as redes neuronais, os algoritmos evolutivos e a aprendizaxe por reforzo.

Study programme competencies
Code Study programme competences
A43 Capacidade para adquirir, obter, formalizar e representar o coñecemento humano nunha forma computable para a resolución de problemas mediante un sistema informático en calquera ámbito de aplicación, particularmente os relacionados con aspectos de computación, percepción e actuación en ambientes ou contornos intelixentes.
B1 Capacidade de resolución de problemas
B3 Capacidade de análise e síntese
B9 Capacidade para xerar novas ideas (creatividade)
C6 Valorar criticamente o coñecemento, a tecnoloxía e a información dispoñible para resolver os problemas cos que deben enfrontarse.
C8 Valorar a importancia que ten a investigación, a innovación e o desenvolvemento tecnolóxico no avance socioeconómico e cultural da sociedade.

Learning aims
Learning outcomes Study programme competences
Develop an autonomous control system for its operation in a real environment A43
 B1
 C6
Know the non-resolved problems in autonomous robotics A43
 B1
B9
 C6
C8
Know the problems of sensing and actuation in systems that operate in the real world and real time A43
 B1
 C6
Know the problems of knowledge representation in autonomous robotics A43
 B1
B9
 C6
Know the problems to tackle when an autonomous robotic control system is developed A43
 B1
B3
B9
 C6
C8

Contents
Topic Sub-topic
Introduction to autonomous robotics ¿What is an autonomous robot?
History
Sensors and actuators
Behaviors
Planning
Learning and evolution
Elements of a robotic system Robotic system
Actuators and effectors
Sensors
Control architectures
Behavior-based robotics Antecedents
Classical control architectures
Control architectures
Knowledge-based robotics Knowledge
Traditional deliberative robotics
Navigation
Hybrid approximations Main hybrid architectures
Cognitive robotics
Evolutionary robotics Evolutionary algorithms
Application to robotics
Learning in autonomous robotics Learning in classifier systems
Reinforcement learning: Q-learning
Combination of reinforcement and connectionist learning

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Laboratory practice A43 B9 B1 21 21 42
Supervised projects B1 B3 B9 C6 C8 0 30 30
Oral presentation B3 B9 C8 4 28 32
Guest lecture / keynote speech C8 C6 21 21 42
 
Personalized attention 4 0 4
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Laboratory practice Lab. sessions in which the teachers will explain the robotic platform and its development software in detail. Moreover, during these sessions, the students must perform the design, implementation and validation of the supervised projects under the supervision of a teacher.
Supervised projects Programming exercises that must be developed using the selected robotic platform. These exercises will be carried out in an autonomous way and their progress will be supervised by the teachers
Oral presentation Theoretical work about a specific topic from the contents that will be orally presented and discussed with other students
Guest lecture / keynote speech Oral exposition by the teachers of the theory of the subject.

Personalized attention
Methodologies
Laboratory practice
Supervised projects
Oral presentation
Description
During the lab practices and tutorials, the student can consult the teacher all the doubts that appear about the realization of the formulated practical problems or about the use of the simulator or the real robot.

Supervised projects: It is recommendable the use of a personal assistance in these activities to resolve conceptual doubts or procedures than can appear during the resolution of the practical problems. Also, the personal assistance will be focused on in the explanation, by the student, of the proposed solution.

Oral presentation: the students' progress in their theoretical work must be supervised by the teachers, both in terms of contents and format.

Assessment
Methodologies Competencies Description Qualification
Laboratory practice A43 B9 B1 The attendance to the laboratory classes will be considered in the final mark 5
Guest lecture / keynote speech C8 C6 The attendance to the keynote speeches will be considered in the final mark 5
Supervised projects B1 B3 B9 C6 C8 Different programming projects will be proposed along the course that must be carried out in an autonomous way by the student and that will be presented and explained to the teachers afterwards. It is mandatory to pass this methodology independently in order to pass the whole subject. 50
Oral presentation B3 B9 C8 The oral presentation, the participation in the discussion and the written inform will be considered in the final mark. It is mandatory to pass this methodology independently in order to pass the whole subject. 40
 
Assessment comments
<p> Evaluation of this course is based on independently overcoming the two main methodologies: supervised projects and oral presentation. The first one focuses on the practical demonstration of the knowledge and skills acquired to solve problems in autonomous robotics, and the second one in the completion and presentation of a paper on a specific topic within theoretical agenda. Thus, if the student does not pass the subject in the ordinary call, he / she shall repeat all activities that were not passed in the extraordinary call. As an example, if a student passed the oral presentation but failed the supervised projects, he / she shall repeat these. Students with part-time enrollment can displace the 5% of the qualification of the attendance to the other activities, both in theory and in practice, in case they can not regularly attend classes. This change in the qualification methodology shall be applied to teachers of the subject at the beginning of the course. </p>

Sources of information
Basic Bekey, A. (2005). Autonomous Robots. MIT Press
Arkin, R.C. (1998). Behavior Based Robotics. MIT Press
Santos, J., Duro, R.J. (2005). Evolución Artificial y Robótica Autónoma. RA-MA
Mataric, Maja J. (2007). The Robotics Primer. MIT Press
Complementary Santos, J. (2007). Vida Artificial. Realizaciones Computacionales. ServicioPublicaciones UDC
Floreano, D. and Mattiussi, C. (2008). Bio-Inspired Artificial Intelligence. Tema 7. MIT Press
Salido, J. (2009). Cibernética aplicada. Robots educativos. Ra-Ma
Nolfi, S., Floreano, D. (2000). Evolutionary Robotics. MIT Press
Thurn, S., Burgard, W., Fox, D. (2005). Probabilistic Robotics. MIT Press
Sutton, R.S., Burton A.G. (1998). Reinforcement Learning. MIT Press
Pfeifer, R. and Scheier, C. (1999). Understanding Intelligence. MIT Press

Recommendations
Subjects that it is recommended to have taken before
Intelligent Systems/614G01020
Knowledge Representation and Automatic Reasoning/614G01036
Intelligent Systems Development/614G01037
Machine Learning/614G01038

Subjects that are recommended to be taken simultaneously

Subjects that continue the syllabus

Other comments
&lt;div&gt;Para axudar a conseguir unha contorna inmediata sustentable e cumprir co obxectivo da acción número 5: &quot;Docencia e investigación saudable e sustentable ambiental e social&quot; do &quot;Plan de Acción Green Campus Ferrol&quot; a entrega dos traballos documentais que se realicen nesta materia:&amp;nbsp;&lt;/div&gt;&lt;div&gt;&lt;p&gt;1. Solicitarase en formato virtual e/ou soporte informático&amp;nbsp;&lt;/p&gt;&lt;p&gt;2. Realizarase a través de Moodle, en formato dixital sen necesidade de imprimilos&amp;nbsp;&lt;/p&gt;&lt;p&gt;3. De se realizar en papel:&amp;nbsp;&lt;/p&gt;&lt;p&gt;- Non se empregarán plásticos.&amp;nbsp;&lt;/p&gt;&lt;p&gt;- Realizaranse impresións a dobre cara.&amp;nbsp;&lt;/p&gt;&lt;p&gt;- Empregarase papel reciclado.&amp;nbsp;&lt;/p&gt;&lt;p&gt;- Evitarase a impresión de borradores.&lt;/p&gt;&lt;/div&gt;


(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.