Students should have a solid background in computer programming and algorithms, and basic knowledge in calculus, linear algebra, and statistics. Such background and knowledge should have been obtained through the completion of the corresponding first-year courses.
Assignments will require the use of Python programming language, and the completion of the Intelligent Systems course is highly recommended.
Any experience with any modern procedural language (e.g. C++) should be sufficient in any case.
Assignments and/or seminar may involve the use of Linux as operating system, so the completion of the Operating Systems course is highly recommended
This course will introduce students to the fundamental constraints, technologies, and algorithms of autonomous robotics. The focus will be on computational aspects of autonomous wheeled mobile robots. The most important themes will be mobility, perception, localization, and navigation. Assignments will require the implementation of behaviours suitable for being deployed in Mobile wheeled robots like the AWS Deep Racer car or the Pepper SoftBank Robotics Robot.
Course competences | |
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Code | Description |
CM02 | Ability to know the theoretical fundamentals of programming languages, and their associated techniques for lexical, syntactic, and semantic processes, along with their application in the creation, design, and language processing. |
CM04 | Ability to know the fundamentals, paradigms, and techniques of intelligent systems, and analyse, design, and build systems, services, and digital, applications which could use such techniques in any application context. |
CM07 | Ability to know and develop computational learning techniques, and design and implement applications and systems which could use them, including the ones for the automatic extraction of information and knowledge from great batches of information. |
INS04 | Problem solving skills by the application of engineering techniques. |
PER01 | Team work abilities. |
PER02 | Ability to work in multidisciplinary teams. |
PER03 | Ability to work in an international context. |
SIS03 | Autonomous learning. |
SIS08 | Initiative and entrepreneurial abilities. |
UCLM01 | Command of a second language at a B1 level within the Common European Framework of Reference for Languages |
Course learning outcomes | |
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Description | |
Design and programming of basic and advanced behaviors that allow a robot to function autonomously in a specific environment. | |
Improvement of communication skills of the student in English language | |
Additional outcomes | |
Not established. |
Training Activity | Methodology | Related Competences (only degrees before RD 822/2021) | ECTS | Hours | As | Com | Description | |
Class Attendance (theory) [ON-SITE] | Lectures | CM04 INS04 SIS03 | 0.78 | 19.5 | Y | N | Theory | |
Computer room practice [ON-SITE] | Practical or hands-on activities | CM02 CM04 CM07 INS04 PER01 | 0.9 | 22.5 | Y | N | Practices based on theoretical topics | |
Workshops or seminars [ON-SITE] | Workshops and Seminars | CM07 INS04 PER02 PER03 SIS08 | 0.36 | 9 | Y | N | Practical cases and discussions | |
Project or Topic Presentations [ON-SITE] | Group Work | PER01 PER02 SIS08 UCLM01 | 0.18 | 4.5 | Y | N | Presentation and discussion of team work | |
Individual tutoring sessions [ON-SITE] | Lectures | CM02 CM04 CM07 | 0.18 | 4.5 | N | N | Tutoring | |
Writing of reports or projects [OFF-SITE] | Group Work | CM02 CM04 CM07 INS04 PER01 PER02 | 1.8 | 45 | Y | N | Team work development and writting | |
Study and Exam Preparation [OFF-SITE] | Self-study | CM02 CM04 CM07 INS04 SIS03 | 1.8 | 45 | Y | N | Deliveries | |
Total: | 6 | 150 | ||||||
Total credits of in-class work: 2.4 | Total class time hours: 60 | |||||||
Total credits of out of class work: 3.6 | Total hours of out of class work: 90 |
As: Assessable training activity Com: Training activity of compulsory overcoming (It will be essential to overcome both continuous and non-continuous assessment).
Evaluation System | Continuous assessment | Non-continuous evaluation * | Description |
Progress Tests | 25.00% | 40.00% | [PRES][ESC] - Continuous assessment: The evaluation of this activity is IN GROUPS Oral presentation in class and questions about a work already documented and submitted - Non-continuous evaluation The evaluation of this activity is INDIVIDUAL Theoretical exam |
Theoretical papers assessment | 15.00% | 30.00% | [INF] - Continuous assessment / Non-continuous evaluation The evaluation of this activity is IN GROUPS Evaluation of a memory about a work previously submitted |
Laboratory sessions | 40.00% | 30.00% | [LAB] - Continuous assessment / Non-continuous evaluation The evaluation of this activity is INDIVIDUAL Evaluation of the submissions resulting the from laboratory practices |
Assessment of active participation | 20.00% | 0.00% | [PRES] - Continuous assessment: The evaluation of this activity is INDIVIDUAL Active participation during activities of relevant importance like seminars |
Total: | 100.00% | 100.00% |
Not related to the syllabus/contents | |
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Hours | hours |
Workshops or seminars [PRESENCIAL][Workshops and Seminars] | 9 |
Project or Topic Presentations [PRESENCIAL][Group Work] | 4.5 |
Individual tutoring sessions [PRESENCIAL][Lectures] | 4.5 |
Writing of reports or projects [AUTÓNOMA][Group Work] | 45 |
Study and Exam Preparation [AUTÓNOMA][Self-study] | 45 |
Unit 1 (de 5): Introduction | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 7.5 |
Computer room practice [PRESENCIAL][Practical or hands-on activities] | 4.5 |
Unit 2 (de 5): Mobility | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 1.5 |
Computer room practice [PRESENCIAL][Practical or hands-on activities] | 4.5 |
Unit 3 (de 5): Perception | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 4.5 |
Computer room practice [PRESENCIAL][Practical or hands-on activities] | 4.5 |
Unit 4 (de 5): Localization | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 3 |
Computer room practice [PRESENCIAL][Practical or hands-on activities] | 4.5 |
Unit 5 (de 5): Advanced Topics | |
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Activities | Hours |
Class Attendance (theory) [PRESENCIAL][Lectures] | 3 |
Computer room practice [PRESENCIAL][Practical or hands-on activities] | 4.5 |
Global activity | |
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Activities | hours |
General comments about the planning: | This course schedule is APPROXIMATE. It could vary throughout the academic course due to teaching needs, bank holidays, etc. A weekly schedule will be properly detailed and updated on the online platform (Virtual Campus). Note that all the lectures, practice sessions, exams and related activities performed in the bilingual groups will be entirely taught and assessed in English. Classes will be scheduled in 3 sessions of one hour and a half per week. The assessment activities could be performed in the afternoon, in case of necessity. |
Author(s) | Title | Book/Journal | Citv | Publishing house | ISBN | Year | Description | Link | Catálogo biblioteca |
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Bekey, George A. | Autonomous robots : from biological inspiration to implement | The Mit Press | 0-262-02578-7 | 2005 | An introduction to the science and practice of autonomous robots that reviews over 300 current systems and examines the underlying technology. |
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Fahimi, Farbod | Autonomous robots : modeling, path planning, and control | Springer | 978-0-387-09537-0 | 2009 | Autonomous Robots: Modeling , Path Planning, and Control is suitable for mechanical and electrical engineers who want to familiarize themselves with methods of modeling/analysis/control that have been proven efficient through research. This book presents the theoretical tools for analyzing the dynamics of and controlling Autonomous Robots in a form comprehensible for students and engineers. |
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Frank L. Lewis, Shuzhi Sam Ge | Autonomous Mobile Robots: Sensing, Control, Decision Making and Applications | CRC Press | 978-0367390891 | 2019 | It has long been the goal of engineers to develop tools that enhance our ability to do work, increase our quality of life, or perform tasks that are either beyond our ability, too hazardous, or too tedious to be left to human efforts. Autonomous mobile robots are the culmination of decades of research and development, and their potential is seemingly unlimited. | ||||
Nikolaus Correll | Introduction to Autonomous Robots | Magellan Scientific | 978-0692700877 | 2020 | This book introduces concepts in mobile, autonomous robotics to 3rd-4th year students in Computer Science or a related discipline. The book covers principles of robot motion, forward and inverse kinematics of robotic arms and simple wheeled platforms, perception, error propagation, localization and simultaneous localization and mapping. The cover picture shows a wind-up toy that is smart enough to not fall off a table just using intelligent mechanism design and illustrate the importance of the mechanism in designing intelligent, autonomous systems. This book is open source, open to contributions, and released under a creative common license. | https://github.com/correll/Introduction-to-Autonomous-Robots | |||
Niku, Saeed B. (Saeed Benjamin) | Introduction to robotics : analysis, control, applications | Wiley | 978-0-470-60446-5 | 2010 | Niku offers comprehensive, yet concise coverage of robotics that will appeal to engineers. Robotic applications are drawn from a wide variety of fields. Emphasis is placed on design along with analysis and modeling. Kinematics and dynamics are covered extensively in an accessible style. Vision systems are discussed in detail, which is a cutting-edge area in robotics. Engineers will also find a running design project that reinforces the concepts by having them apply what they've learned. |
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Thrun, Sebastian | Probabilistic robotics | The MIT Press | 0-262-20162-3 | 2005 | Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. |
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