Ing. Filip Orság, Ph.D.

Department of Intelligent Systems (UITS)

Of all faculties

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

There are no prerequisites

Not applicable.

Not applicable.

1. Craig, J., J.: Introduction to Robotics: Mechanics and Control, Prentice Hall, 2003, ISBN 0201543613
2. Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2000,  ISBN 0262133830
3. Šolc, F.: Robotické systémy, VUT v Brně, 1990

1. Nolfi, S., Floreano, D.: Evolutionary Robotics : The Biology, Intelligence, and Technology of Self-Organizing Machines (Intelligent Robotics and Autonomous Agents), Bradford Books, 2004, ISBN 0262640562
2. Holland, J., M.: Designing Autonomous Mobile Robots: Inside the Mind of an Intelligent Machine, 2003, ISBN 0750676833
3. Craig, J., J.: Introduction to Robotics: Mechanics and Control, Prentice Hall, 2003, ISBN 0201543613
4. Sciavicco, L., Siciliano, B.: Modelling and Control of Robot Manipulators (Advanced Textbooks in Control and Signal Processing), Springer Verlag, 2000, ISBN 1852332212
5. Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2000,  ISBN 0262133830 
6. Laumond, J., P.: Planning Robot Motion, Springer-Verlag, 1998, ISBN 3540762191  
7. Spong, M., Vydyasagar, M.: Robot Dynamics and Control, J. Willey, 1989, ISBN 047161243X

Not applicable.

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

English

Not applicable.

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. Models and control of the stationary robots.
5. Effectors,sensors and power supply of robots. Applications of the cameras, laser distance meters, and sonars.
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.

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.

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.

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

• Programme IT-MGR-2 Master's

  branch MBI , any year of study, winter semester, 5 credits, elective
  branch MPV , any year of study, winter semester, 5 credits, elective
  branch MGM , any year of study, winter semester, 5 credits, elective
  branch MSK , any year of study, winter semester, 5 credits, elective
  branch MIS , any year of study, winter semester, 5 credits, elective
  branch MBS , any year of study, winter semester, 5 credits, elective
  branch MIN , any year of study, winter semester, 5 credits, compulsory-optional
  branch MMI , any year of study, winter semester, 5 credits, elective
  branch MMM , any year of study, winter semester, 5 credits, elective
  

• Programme IT-MGR-1H Master's

  branch MGH , any year of study, winter semester, 5 credits, recommended