Course detail

Robotics (in English)

FIT-ROBaAcad. year: 2025/2026

Basic components of the stationary industrial robots. Kinematics. Solution of the inverse kinematic task. Equations of motion. Path planning. Elements and structure of the mobile robots. Models and control of mobile robots. Sensoric systems of mobile robots. Localization and navigation. Environment maps. Robot control.

Language of instruction

English

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

Ing. Jaroslav Rozman, Ph.D.

Department

Department of Intelligent Systems (UITS)

Offered to foreign students

Of all faculties

Entry knowledge

Not applicable.

Rules for evaluation and completion of the course

  1. Graded laboratories.
  2. Mid-term written test.
  3. Evaluated project.

There are compulsory projects and laboratories that follow on from the projects.

Aims

To inform students about current state and future of robotics. Also, to inform students about peculiarities of robotic systems and prepare them for introduction, creation and maintaining of robotic systems into practice.


The students acquire knowledge of current state and trends in robotics. Also, they acquire practical knowledge from construction, programs and use of robots.

Study aids

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2019, ISBN 9780262038485 (EN)
Choset, H., Lynch, K. M., Hutchinson, S. et al.: Principles of Robot Motion. MIT, Press, 2005. ISBN 0-262-03327-5.  (EN)
Siegwart, R. a Nourbakhsh, I. R.: Introduction to Autonomous Mobile Robots. MIT Press, 2011. ISBN-13: 978-0262015356  (EN)
Šolc, F.: Robotické systémy, VUT v Brně, 1990  (CS)
Thrun, S., Burgard, W. a Fox, D.: Probabilistic Robotics. MIT Press, 2005. ISBN 0-262-201623  (EN)

Recommended reading

George A. Bekey: Autonomous Robots: From Biological Inspiration to Implementation and Control, 2005, Bradford Book, ISBN-13 978-0262025782
John M. Holland: Designing Autonomous Mobile Robots: Inside the Mind of an Intelligent Machine, 2003, Newnes,  ISBN-13 ‏ 978-0750676830 
Alex Ellery: Planetary Rovers: Robotic Exploration of the Solar System, Springer, 2016, ISBN-13 ‏978-3642032585
Beard and McLain: Small Unmanned Aircraft: Theory and Practice, Princeton, 2021, ISBN-13 ‎ 978-0691149219
Dorf and Bishop: Modern Control Systems, Pearson Hall, 2011, ISBN-13 ‎ 978-0136024583
Franklin, Powel and Emami-Naeini: Feedback Control of Dynamic Systems, Pearson, ISBN13 978-0-13-349659-8
Gary Bradsky and Adrian Kaehler: LearningOpenCV, O'Reilly, 2008, ISBN 978-0-596-51613-0
Grewal, Andrews and Bartone: Global Navigation Satellite Systems, Inertial Navigation, and Integration, Wiley, 2013, ISBN-13 ‎ 978-1118447000
Hassan K. Khalil: Nonlinear Systems, Pearson, ISBN-13 ‎ 978-0130673893
Kaplan and Hegarty: Understanding GPS/GNSS: Principles and Applications, Artech House, 2017, ISBN-13 ‎ 978-1630810580
Ogata: Modern Control Engineering, Pearson, 2009, ISBN-13 ‎ 978-0136156734
Ronald C. Arkin: Behavior-Based Robotics, Bradford Books, 1998, ISBN-13 ‏ : ‎ 978-0262529204
Russel and Norvig: Artificial Intelligence: A Modern Approach, Pearson, 2009, ISBN-13 ‏978-0136042594
Sayed: Fundamentals of Adaptive Filtering, Wiley, 2003, ISBN-13 ‏978-0471461265

Classification of course in study plans

  • Programme IT-MGR-1H Master's

    specialization MGH , 0 year of study, winter semester, recommended course

  • Programme MIT-EN Master's 0 year of study, winter semester, elective

  • Programme MITAI Master's

    specialization NSEC , 0 year of study, winter semester, elective
    specialization NISY up to 2020/21 , 0 year of study, winter semester, elective
    specialization NNET , 0 year of study, winter semester, elective
    specialization NMAL , 0 year of study, winter semester, elective
    specialization NCPS , 0 year of study, winter semester, elective
    specialization NHPC , 0 year of study, winter semester, elective
    specialization NVER , 0 year of study, winter semester, elective
    specialization NIDE , 0 year of study, winter semester, compulsory
    specialization NISY , 0 year of study, winter semester, elective
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NSPE , 0 year of study, winter semester, elective
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NBIO , 0 year of study, winter semester, elective
    specialization NSEN , 0 year of study, winter semester, elective
    specialization NVIZ , 0 year of study, winter semester, elective
    specialization NGRI , 0 year of study, winter semester, elective
    specialization NADE , 0 year of study, winter semester, elective
    specialization NISD , 0 year of study, winter semester, elective
    specialization NMAT , 0 year of study, winter semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Jaroslav Rozman, Ph.D.
Ing. Jan Beran

Syllabus

  1. History, evolution, and current trends in robotics. Introduction to robotics. Robotic applications. Robotic competitions.
  2. Kinematics and statics. Direct and inverse task of kinematics.
  3. Path planning in the cartesian coordinate system.
  4. Effectors,sensors and power supply of robots. Applications of the cameras, laser distance meters, and sonars.
  5. Midterm test.
  6. Basic parameters of the mobile robots. Model and control of the wheel mobile robots.
  7. Robotic middleware. Robot Operating System (ROS), philosophy of ROS, nodes and communication among them.
  8. Maps - configuration space and 3D models.
  9. Probability in robotics. Introduction. Bayesian filtering, Kalman and particle filters. Model of robot movements and measurement model.
  10. Methods of the global and local localization. GPS based localization, Monte Carlo method.
  11. Map building. Algorithms for simultaneous localization and mapping (SLAM).
  12. Trajectory planning in known and unknown environment. Bug algorithm, potential fields, visibility graphs and probabilistic methods.
  13. Introduction to control and regulation.

Laboratory exercise

12 hod., optionally

Teacher / Lecturer

Ing. Jaroslav Rozman, Ph.D.
Ing. Daniel Bambušek

Syllabus

  1. Basic work with Arduino
  2. Working with sensors
  3. Motor control
  4. Basics of ROS, sensor reading
  5. Advanced work in ROS
  6. Final task

Project

14 hod., compulsory

Teacher / Lecturer

Ing. Jaroslav Rozman, Ph.D.

Syllabus

Project implemented on the robot from FIT.