Logo UAB
2021/2022

Robotics in the Smart City

Code: 104553 ECTS Credits: 6
Degree Type Year Semester
2503743 Management of Smart and Sustainable Cities OT 3 2
The proposed teaching and assessment methodology that appear in the guide may be subject to changes as a result of the restrictions to face-to-face class attendance imposed by the health authorities.

Contact

Name:
Carles Pedret Ferré
Email:
Carles.Pedret@uab.cat

Use of Languages

Principal working language:
catalan (cat)
Some groups entirely in English:
No
Some groups entirely in Catalan:
No
Some groups entirely in Spanish:
No

Teachers

Joan Oliver Malagelada
Carles Soler Puig
Carles Pedret Ferré

Prerequisites

The subject does not formally require any pre-requisite. However, for its best understanding, it is advisable to have passed the subjects of Mathematics, Foundations on Informatics, and Instrumentation and Sensors of the first course, and Digitalization and Microcontrollers of the second year.

Objectives and Contextualisation

The objectives of this subject are framed in the application of Robotics in the field of smart city. In particular, it is intended:

  • Provide the student with an overview of the basic concepts of robotics, artificial intelligence and internet of thinks.
  • Ask the student to reflect on the ethical, social and economic implications of the application of robots in the city and intelligent industry.
  • Apply robotic solutions to various current problems in the city.

Competences

  • Carry out projects related to the management, equality and sustainability of cities applying elements of technological innovation such as ICT.
  • Critically analyse work carried out and demonstrate a desire to improve.
  • Demonstrate creativity, initiative and sensitivity in the different social and environmental topic areas.
  • Design platforms of management, integration of public and government services applying technologies and systems of sensorization, acquisition, processing and communication of data.
  • Generate innovative and competitive proposals in professional activity.
  • Identify and interpret social, economic, technological and sustainability challenges in different areas such as: town planning, infrastructures, mobility, urban economies, services and equipment, cultural diversity and social inequality, energy and natural resources, waste, etc.
  • Integrate cyberphysical systems based on the interrelationship between information technology and physical processes in urban environments.
  • Students must be capable of applying their knowledge to their work or vocation in a professional way and they should have building arguments and problem resolution skills within their area of study.
  • Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
  • Students must be capable of communicating information, ideas, problems and solutions to both specialised and non-specialised audiences.
  • Work cooperatively in complex and uncertain environments and with limited resources in a multidisciplinary context, assuming and respecting the role of the different members of the group.

Learning Outcomes

  1. Critically analyse work carried out and demonstrate a desire to improve.
  2. Define sustainable projects based on socially sustainable and equitable robotic contributions.
  3. Demonstrate creativity, initiative and sensitivity in the different social and environmental topic areas.
  4. Describe essential robotic systems in the smart city and apply these to new services for citizens.
  5. Develop the ability to integrate robotic-system solutions in urban and industrial environments.
  6. Generate innovative and competitive proposals in professional activity.
  7. Identify and analyse the ethical issues and socio-economic repercussions associated with the presence of robots in the context of the smart city.
  8. Identify and analyse the paradigm shift in industry, mobility and assistance deriving from autonomous systems.
  9. Identify the challenges of social transformation resulting from the escalation of robotics in the smart city.
  10. Identify the integration processes associated with the transformation of the urban environment following the impact of robotics in logistics, mobility, service development, etc.
  11. Identify the unresolved problems generated by industrial transformation through the ubiquitous appearance of robots.
  12. Students must be capable of applying their knowledge to their work or vocation in a professional way and they should have building arguments and problem resolution skills within their area of study.
  13. Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
  14. Students must be capable of communicating information, ideas, problems and solutions to both specialised and non-specialised audiences.
  15. Work cooperatively in complex and uncertain environments and with limited resources in a multidisciplinary context, assuming and respecting the role of the different members of the group.

Content

The contents of the subject are divided into the following blocks:

Block 1. Theoretical and technical fundamentals:

    1. Classic views of robotics.
    2. Basic technologies: interaction and connectivity. Human-machine interaction components.
    3. Fundamentals of Artificial Intelligence and internet of thinks.
    4. Case study 1. Robotics and the Internet of things.

Block 2. Ethical, social and economic implications:

    1. Ethical issues that arise from the proliferation of robots in the industrial and urban environment.
    2. Industrial Shift: employability in the context of ubiquous robotics and sustainability models.
    3. Case study 2. Impact of artificial intelligence on urban mobility.

Block 3. Applications of robotics.

    1. Case study 3. Industry 4.0 and robotics. Challenges for the insertion of the robot in industrial fields, systems of interaction and collaboration with interconnected, interactive and collaborative robots. Challenges for the insertion of the robot in urban environments.

Methodology

The teaching methodology to be followed is oriented to the student's learning of the subject on an ongoing basis. This process is based on the realization of three types of activities that will be developed throughout the course: theory lectures, problem seminars and case studies and laboratory practicum.

  • Theory lectures: the teacher will provide information on the knowledge of the subject and on strategies to acquire, expand and organize this knowledge. The active participation of the students during these sessions will be encouraged, for example by raising discussions in those points that have a higher conceptual load.
  • Problem seminars and case studies: students will have to actively participate to consolidate the knowledge acquired by solving, presenting and discussing problems and case studies. The transversal competences T01, T03 and T05 will be evaluated in the papers presented in the case studies by carrying out a critical analysis of the work done by each member of the team and the total work presented. This part will have a 5% to the grade of each of the case studies.
  • Laboratory practicum. Students will work as a group in the development of laboratory practicum related to the use of computer and robotic tools.

Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.

Activities

Title Hours ECTS Learning Outcomes
Type: Directed      
Case study seminars 12 0.48 2, 3, 6, 14
Laboratory sessions 12 0.48 1, 4, 5, 10, 15
Theory sessions 26 1.04 5, 10, 9, 8, 7, 11, 12, 13
Type: Supervised      
Tutories 5 0.2
Type: Autonomous      
Preparation of oral presentations 35 1.4 1, 3, 6, 12, 13, 15
Preparation of reports in writing 60 2.4 1, 2, 3, 6, 9, 12

Assessment

The evaluation of the subject will be done progressively and continuously throughout the semester. The evaluation system is based on the following rules:

a) Scheduled evaluation process and activities

 The following activities are foreseen, related to the realization of several works and practices that contain the development and discussion of the different study cases proposed in the course as well as their oral presentation:

Activity A1. Development of the case study 1. This activity consists in carrying out a group of critical work in which the application of the case study 1 is discussed and developed.
Activity A2. Presentation and oral defense of the case study 1. The solution proposed by each group in the case study will be defended by the group in an oral presentation before the class.
Activity A3. Resolution of laboratory practices of Block 1. This activity consists of the resolution of the statement of practices formulated for this block.
Activity B1. Development of the case study 2. This activity consists of carrying out in a group a critical work where the application of the case study 2 is discussed and developed.
Activity B2. Presentation and oral defense of the case study 2. The solution proposed by each group in the case study will be defended by the group in an oral presentation before the class.
Activity B3. Resolution of laboratory practices of Block 2. This activity consists of the resolution of the statement of practices formulated for this block.
Activity C1. Development of the case study 3. This activity consists of carrying out in a group a critical work where the application of the case study 3 is discussed and developed.
Activity C2. Presentation and oral defense of the case study 3. The solution proposed by each group in the case study will be defended by the group in anoral presentation before the class.
Activity C3. Resolution of laboratory practices of Block 3. This activity consists of the resolution of the statement of practices formulated for this block.

The final grade will be calculated in the following way:

                                                                               MarkBlock1 = 20% MarkWork1 (Act. A1) + 50% MarkPresentation1 (Act A2) + 30% PracticumComputer (Act A3)

                                                                               MarkBlock2 = 20% MarkWork2 (Act. B1) + 50% MarkPresentation2 (Act B2) + 30% PracticumComputer (Act B3)

                                                                               MarkBlock3 = 20% MarkWork3 (Act. C1) + 50% MarkPresentation3 (Act. C2) + 30% PracticumComputer (Act C3)

                                                                                                                FinalMark = 35% * MarkBlock1 + 35% * MarkBlock2 + 30% * MarkBlock3

To pass the course, you must obtain a minimum grade of 5 as a result of the calculation of final grade (FinalMark). To apply the FinalMark formula it will be necessary to obtain a minimum grade of 3.5 in all grades of the blocks, i.e. each of the grades MarkBlock1, MarkBlock2 and MarkBlock3 must be greater than or equal to 3.5. Therefore, if a MarkBlock is graded with a grade lower than the one indicated above, the subject cannot be passed.

If a student does not reach the minimum grade of 3.5 in any of the MarkBlock and for this reason does not pass the course, the final grade will be a maximum of 4.5, i.e. it will be equal to the value of the weighted average if FinalMark is less than 4.5 or 4.5 if it is higher.

b) Programming evaluation activities

 The scheduling of the evaluation activities will be given on the first day of the subject and will be made public through the Virtual Campus (Moodle) and on the website of the Engineering School, in the exams section.

c) Make-up process

This course is continuously assessed by means of the presentation of the works that correspond to the study cases and to the practices of laboratory. Papers must be submitted on a date and form according to the instructions provided by the teacher, who may request a resubmission as a form of make up. Since one MarkBlock can be offset with another, there are no recovery processes at the end of the semester.

d) Procedure for review of qualifications

For each evaluation activity, a place, date and time of revision in which the student can review the activity with the teacher will be indicated. In this context, claims may be made on the activity grade, which will be evaluated by the faculty responsible for the subject. If the student does not show up for this revision, this activity will not be reviewed later.

e) Qualifications

 The final grade of the subject will be calculated according to the percentages mentioned in section a) of this point. Keep in mind that:

  • Honor plates. Granting a grade of honor registration is only the decision of the faculty responsible for the subject. The regulations of the UAB indicate that MH can only be granted to students who have obtained a final grade equal to or greater than 9.00.
  • Not evaluable. A student who has not submitted to any Activity will be considered "non-evaluable". In any other case, the evaluation criteria detailed above are followed.

f) Irregularities by the student, copy and plagiarism

Without prejudice to other disciplinary measures deemed appropriate, the irregularities committed by the student that may lead to a variation of the grade of an evaluation act will be scored with a zero. Therefore, copying, plagiarism, cheating, letting copy, etc. in any of the evaluation activities will involve suspending it with a zero. If it is necessary to pass any of these evaluation activities to pass the subject, this subject will be suspended directly, without the opportunity to recover it in the same course.

g) Evaluation of repeating students

No mark is saved from one course for the next. Repeating students follow the same evaluation standards as any other student.

Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Laboratory reports 30% 0 0 1, 3, 4, 5, 10, 15
Oral Presentations 50% 0 0 2, 3, 6, 14, 13
Reports from case studies 20% 0 0 1, 2, 6, 9, 8, 7, 11, 12, 13

Bibliography

Platform used for communication with students: Moodle.

Basic bibliography:

  • A. Barrientos. Foundations of Robotics, McGraw-Hill, 2007.
  • J. R. Mercader Uguina. The future of work in the era of digitization and robotics, Tirant Lo Blanch, 2017.
  • International Journal of Social Robotics, Springer-Verlag, online magazine.
  • Concha Bielza, A. Mateos and S. Ríos, Fundamentals of Decision Aid Systems, Ed. Ra-Ma, 2002.
  • VV.AA. Artificial intelligence A Modern Approach, Prentice-Hall, 1996.
  • T.S. Kuhn. The structure of Scientific Revolutions: 50th Aniversary Edition. The University of Chicago Press. 2012

Software

In Block 1 (Theoretical and technical fundamentals): Node-Red