Course details

Robotics (in English)

ROBa Acad. year 2021/2022 Winter semester 5 credits

Current academic year

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


Course coordinator

Language of instruction



Examination (written)

Time span

  • 26 hrs lectures
  • 6 hrs laboratories
  • 20 hrs projects

Assessment points

  • 55 pts final exam
  • 19 pts mid-term test (written part)
  • 6 pts numeric exercises
  • 20 pts projects




Subject specific learning outcomes and competences

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

Learning objectives

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

Why is the course taught

Robotics experiences a big boom thanks to coming of various autonomous systems, be it autonomous vehicles or mass production. General knowledge of dealing with various tasks and basics of robotics clears the way to employment in the fields, which use robots on a daily basis.

Study literature

  • 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 

Fundamental literature

  • Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2019, ISBN 9780262038485

Syllabus of lectures

  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. Probability in robotics. Introduction. Bayesian filtering, Kalman and particle filters. Model of robot movements and measurement model.
  9. Methods of the global and local localization. GPS based localization, Monte Carlo method.
  10. Map building. Algorithms for simultaneous localization and mapping (SLAM).
  11. Trajectory planning in known and unknown environment. Bug algorithm, potential fields, visibility graphs and probabilistic methods.
  12. Introduction to control and regulation.
  13. Multicopters, principle, control, properties, usage. Human - robot collaboration.

Syllabus of laboratory exercises

  1. Lego Mindstorms
  2. Basics of ROS, sensor reading
  3. Advanced work in ROS

Syllabus - others, projects and individual work of students

Project implemented on some of the robots from FIT.

Progress assessment

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

Course inclusion in study plans

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