Language of Instruction:Czech
Private info:http://www.fit.vutbr.cz/study/courses/ROB/private/
Completion:examination (written)
Type of
Guarantor:Orság Filip, Ing., Ph.D. (DITS)
Lecturer:Orság Filip, Ing., Ph.D. (DITS)
Instructor:Orság Filip, Ing., Ph.D. (DITS)
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
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.
  Basic components of the stationary industrial robots. Kinematic chains. Kinematics. Solution of the inverse kinematic task. Singularities. 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. Man-machine interface, telepresence. AI in robotics. Microrobotics.
Learning outcomes and competencies:
  The students acquire knowledge of current state and trends in robotics. Also, they acquire practical knowledge from construction and use of robots.
Syllabus of lectures:
  1. History, evolution, and current trends in the robotics. Basic robotics. Robotic applications. Hobby robotics.
  2. Overwiev of the stationary and mobile robots. The most famous robotic projects. Use in the civil and military applications. Characteristic parameters, kinematic structures.
  3. Kinematics and statics. Direct and inverse task of kinematics.
  4. Path planning and movement dynamics of the stationary robots.
  5. Models and control of the stationary robots.
  6. Effectors and sensors. Types and their applications.
  7. Basic parameters of the mobile robots. Model and control of the wheel mobile robots.
  8. Basic algorithms of the robotic vision. Applications of the cameras, laser distance meters, and sonars.
  9. Map-building and localisation of the robot. Analysis of the known methods. Examples.
  10. Global and local navigation of the mobile robots. Means of the navigation. Examples.
  11. Methods of the planning and problem solving.
  12. Local and global methods of the path planning. Path planning in a complex environment with obstacles.
  13. Use of the neural networks and other methods for the control and navigation of the robots.
Syllabus of laboratory exercises:
  1. To familiarise with the robotic laboratory.
  2. Monitoring of the sensors of the Trilobot.
  3. Simple programming of the Trilobot.
Syllabus - others, projects and individual work of students:
 Project implemented on the Trilobot focused on the artificial intelligence.
Fundamental literature:
  • 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
  • Holland, J., M.: Designing Autonomous Mobile Robots: Inside the Mind of an Intelligent Machine, 2003, ISBN 0750676833
  • Craig, J., J.: Introduction to Robotics: Mechanics and Control, Prentice Hall, 2003, ISBN 0201543613
  • Sciavicco, L., Siciliano, B.: Modelling and Control of Robot Manipulators (Advanced Textbooks in Control and Signal Processing), Springer Verlag, 2000, ISBN 1852332212
  • Murphy, R., R.: An Introduction to AI Robotics (Intelligent Robotics and Autonomous Agents), Bradford Books, 2000,  ISBN 0262133830 
  • Laumond, J., P.: Planning Robot Motion, Springer-Verlag, 1998, ISBN 3540762191  
  • Spong, M., Vydyasagar, M.: Robot Dynamics and Control, J. Willey, 1989, ISBN 047161243X
Study literature:
  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
Progress assessment:
  1. Mid-term written test.
  2. Evaluated project with a defence.
Exam prerequisites:

Your IPv4 address:
Switch to https

DNSSEC [dnssec]