Intelligent robotics

The course is not on the list Without time-table
Code Completion Credits Range Language
AE3M33IRO Z,ZK 7 3+2c
The course cannot be taken simultaneously with:
Intelligent robotics (A3M33IRO)
Autonomous Robotics (BE3M33ARO)
Autonomous Robotics (B3M33ARO)
The course is a substitute for:
Intelligent robotics (A3M33IRO)
Department of Cybernetics

The subject teaches principles allowing to build robots perceiving surrounding world and activities in it including the abilities to modify it. Various architectures of robots with cognitive abilities and their realizations will be studied. Students will experiment with robots in practical assignments. Studied material is applicable more widely while building intelligent machines.

Syllabus of lectures:

1. Robotics, its historic and societal grounding.

2. Robot kinematics.

3. Robot kinematics. Dynamics. Statics.

4. Different robots, their design, sensors and actuators.

5. Architectures of intelligent robots. Feedback.

6. Inertial sensors, GPS, odometry.

7. Additional sensors (senses) for intelligent robotics.

8. Visual servoing.

9. Representing surrounding world of the robot.

10. Planning in robotics. Discrete planning formalism.

11. Planning as sampling in configuration space (C-space). Planning under constraints.

12. Localization and mapping.

13. Humanoid robots.

Syllabus of tutorials:

1. Introduction to the laboratory. Homework 1 assignment.

2. Consultations, work with robots.

3. Consultations, work with robots.

4. Consultations, work with robots.

Homework 1 handover.

5. Planning tools. Homework 2 assignment.

6. Experiments with planning tasks.

7. Consultations, work with robots.

8. Written test. Consultations, work with robots.

9. Consultations, work with robots. Homework 2 handover.

10. Experiments with sensors for perception. Homework 3 assignment.

11. Consultations, work with robots.

12. Consultations, work with robots.

13. Consultations, work with robots. Homework 3 handover.

14. Written test 2. Credit.

Study Objective:
Study materials:

1. Steven M. LaValle. Planning Algorithms, Cambridge University Press, 2006, 842 s.

2. R. Pfeifer, C. Scheie. Understanding Intelligence, MIT Press, 2002.

3. B. Siciliano, O. Khatib (editoři): Handbook of Robotics, Springer-Verlag, Berlin 2008.

Further information:
No time-table has been prepared for this course
The course is a part of the following study plans:
Data valid to 2019-03-19
For updated information see http://bilakniha.cvut.cz/en/predmet12816004.html