Robotics (in English)

• 26 hrs lectures
• 12 hrs laboratories
• 14 hrs projects

• 55 pts final exam (written part)
• 19 pts mid-term test (written part)
• 12 pts labs
• 14 pts projects

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.

• George A. Bekey: Autonomous Robots: From Biological Inspiration to Implementation and Control, 2005, Bradford Book, ISBN-13 978-0262025782

• Ronald C. Arkin: Behavior-Based Robotics, Bradford Books, 1998, ISBN-13 ‏ : ‎ 978-0262529204

• 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

• 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

• Kaplan and Hegarty: Understanding GPS/GNSS: Principles and Applications, Artech House, 2017, ISBN-13 ‎ 978-1630810580

• Hassan K. Khalil: Nonlinear Systems, Pearson, ISBN-13 ‎ 978-0130673893

• Dorf and Bishop: Modern Control Systems, Pearson Hall, 2011, ISBN-13 ‎ 978-0136024583

• Ogata: Modern Control Engineering, Pearson, 2009, ISBN-13 ‎ 978-0136156734

• Franklin, Powel and Emami-Naeini: Feedback Control of Dynamic Systems, Pearson, ISBN13 978-0-13-349659-8

• Beard and McLain: Small Unmanned Aircraft: Theory and Practice, Princeton, 2021, ISBN-13 ‎ 978-0691149219

• Sayed: Fundamentals of Adaptive Filtering, Wiley, 2003, ISBN-13 ‏978-0471461265

• Russel and Norvig: Artificial Intelligence: A Modern Approach, Pearson, 2009, ISBN-13 ‏978-0136042594

• Siegwart, R. a Nourbakhsh, I. R.: Introduction to Autonomous Mobile Robots. MIT Press, 2011. ISBN-13: 978-0262015356 

• Thrun, S., Burgard, W. a Fox, D.: Probabilistic Robotics. MIT Press, 2005. ISBN 0-262-201623 

• Choset, H., Lynch, K. M., Hutchinson, S. et al.: Principles of Robot Motion. MIT, Press, 2005. ISBN 0-262-03327-5. 

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

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.

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 implemented on the robot from FIT.

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

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