Intelligent Robotics

Prerequisite:

Occupational Safety II KM (35BP2)

The course is a substitute for:

Intelligent Robotics (X33IRO)

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

We will explain how to integrate knowledge from robotics, computer vision, and artificial intelligence to solve a non-trivial engineering task related to intelligent robotics. We will primarily pay attation to the interplay between kinematics, visual and tactile perception, and trajectory planning based on sensoric information. Creative engineering work and its presentation in the form of a technical report willexpected from students.

Requirements:

Required prerequisities are 33KUI and 33OTS. 33ROB and 33PVR are recommended.

Syllabus of lectures:

1. Intelligent robots and their architecture

2. Structure of intelligent robots and their components

3. Odometry, sonars, radars, proximity sensors, range finders

4. Robot vision

5. Bayesian, non-bayesian, Fuzzy andDempster-Schaffer theory of uncertain information

6. Fusion of uncertain information from sensors for the orientation and planning

7. Modelling robot's world

8. Robot behaviour patterns, biological inspirations

9. Robot action planning

10. Accomplishing tasks, active exploration, cooperation of robots

11. Autonomous vehicles

12. Orientation and navigation of autonomous vehicles

13. Examples of existing intelligent robots

14. Demonstration of a real intelligent robot

Syllabus of tutorials:

The goal of the laboratories is to get students familiar with typical tasks which have to be solved by intelligent robots. A couple of students will solve two tasks related (1) to the acquisition and interpretation of sensoric data and (2) to the robot action planning using the sensoric data.

1. Task formulation, tools

2. - 6. Students solve the task related to sensor data acquisition and interpretation

7. Defence of the first task

8. - 12. Students solve the task related to the robot action planning and control

13. Defence of the second task

14. The presentation of the solutions to other students

Study Objective:

Study materials:

(1) Michaelson, H.B.: How to Write and Publish Engineering Papers and Reports. Isi Press, Philadelphia, USA, 1986

(2) Šonka, M., Hlaváč, V., Boyle, R.: Image Processing, Analysis, and Machine Vision. PWS Publishing, 1998

(3) Asada, Slotine, J.-J.E.: Robot Analysis and Control. Willey-Interscience Publication, 1986

(4) Nilsson, J.: Problem-Solving Methods in Artificial Intelligence. McGraw-Hill, 1971

(5) For more information see http://cmp.felk.cvut.cz/cmp/courses/IRO

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Technická kybernetika-inženýrský blok (compulsory course)
• Technická kybernetika-inženýrský blok (compulsory course)