Autonomous robotics

Autonomous robotics

1.

Subject title

Autonomous robotics

Автономна роботика

2.

Code

F23L3W072

3.

Study program

Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Информатичка едукација, Software engineering and information systems, Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Software engineering and information systems, Стручни студии за програмирање, Стручни студии за програмирање,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Прв циклус

6.

Academic year / semester

4 / Зимски

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Андреа Кулаков проф. д-р Невена Ацковска

9.

Prerequisites for enrollment

Основи на роботика или Алгоритми и податочни структури

10.

Subject goals and competencies:


After completing this course, the student is expected to have in-depth knowledge of the development of autonomous robotic systems (autonomous vehicles, autonomous aircraft, etc.) using probabilistic approaches in robotics.

11.

Subject content:


1. Sensors and effectors in autonomous robotics 2. Mathematical principles in autonomous robotics 3. Probabilistic sensor models 4. Probability models of management 5. Kalman filter and its implementations 6. Kalman filter and its implementations 7. Kalman filter and its implementations 8. Mapping 9. Localization 10. Simultaneous mapping and localization 11. Simultaneous mapping and localization 12. Planning and learning in intelligent robotic systems 13. Planning and learning in intelligent robotic systems

12.

Learning methods:


Предавања поддржани со презентации преку слајдови, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

45 hours

16.

Other forms of activities

16.1.

Project tasks

15 hours

16.2.

Independent tasks

15 hours

16.3.

Homework

75 hours

17.

Grading method

17.1.

Tests

10 points

17.2.

Seminar work / project (presentation: written and oral)

15 points

17.3.

Activities and learning

10 points

17.4.

Final exam

70 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

Редовна посета на наставата, навремено предадени домашни и презентација на проектна задача

20.

Language of instruction

Македонски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

No.

Author

Title

Publisher

Year

4185

Sebastian Thurn, Wolfram Burgard, Dieter Fox

Probabilistic Robotics

MIT Press

2005

4186

Roland Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza

Introduction to Autonomous Mobile Robots

MIT Press

2011

22.2.

Additional literature

No.

Author

Title

Publisher

Year