Robotics and machine perception

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

The first part of the subject introduces recent trends in robotics applied in industry and elsewhere. The second part of the subject tackles basic principles of machine perception and its applications in robotics, control systems or quality control.

Requirements:

Syllabus of lectures:

1. Robot as intelligent peripherial device of a computer. Industrial context.

2. Kinematics, statics, dynamics of robots ? an overview.

3. Direct kinematics problem.

4. Inverse kinematics problem.

5. Control systems for robots and their programming.

6. Machine perception and its constituents.

7. Image analysis, taxonomy of methods.

8. Understanding of two-dimensional image.

9. Three-dimensional vision, task formulations, geometry of three-dimensional vision.

10. Reconstruction of three-dimensional scenes, basic ideas.

11. Robot with feedback based on images.

12. Tactile, sound and other feedbacks from outside world.

13. Mobile robots, their control, perception and representation of the outer world.

14. Synthetizing lecture. Industrial and other applications of robots and machine perception

Syllabus of tutorials:

The laboratory exercises will be organized as individual work of a small team consisting of two students extended to the whole semester. The free labs will be available to students and consultations with instructors. This form is dictated by several unique robots available in labs. The first part of the laboratory exercises will be devoted to kinematics of an industrial robot with open kinematic chain and its control. The second part students solve manipulation or welding task with a robot equipped with optical feedback. At the beginning of labs, the task specification will be written by students. Before the credit from a subject is granted, students have to defend their final report.

Study Objective:

Study materials:

1.McKerrow P.J.: Introduction to robotics, Addison Wesley, 1991.

2.Šonka M., Hlaváč V., Boyle R.D. Image Processing, Analysis and Machine Vision, PWS Boston, 1999.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Inteligentní systémy (compulsory elective course)