Sensor-Robot Systems

1.

Subject title

Sensor-Robot Systems

Сензорско-роботски системи (Sensor-Robot Systems)

2.

Code

m23_s_040

3.

Study program

Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Еducation with ICT, Eco-informatics, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software Engineering, IT management, Bioinformatics, Security, Cryptography and Coding, Software Engineering, Data science in computer science and engineering, Cloud Computing, Statistics and Data Analytics, Inteligent Systems, Software for embedded systems,

4.

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

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Андреа Кулаков

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

The student will be capable of modeling and implementing integrated robotic - Sensor systems, especially integration of wireless sensor networks with robotic systems.

11.

Subject content:

Introduction to sensor-robotic systems. Agriculture and Classification of Data in Wireless sensor networks. Application of methods of artificial intelligence. Management systems with Data in wireless sensor networks. Managing data in powerful wireless sensor networks. Sound processing systems in sensor networks and robots. Systems for Processing of video signals in sensor networks and robots. Communication between the nodes in network and robots. Networked info-mechanical systems. Covering and researching over Setting sensor networks. Navigation of moving robots with the help of a sensor network. Assigning tasks to multi-robotic systems mediated by the sensor network. Coordination and model of trust in multi-robotic systems. Learning in multiple-robotic Systems. Biologically inspired robots lined with the environment. Robotic development architectures. Theories of development and their application in robotics. Feeling for yourself. Perceiving. Perceiving objects in the environment. Perceiving the space. Perceiving others agents in the surroundings. Social learning. Motivations and internal values ??in autonomous agents.

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 и семинарска работа, учење во електронско опкружување (форуми, консултации)

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

60 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

0 hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

0 points

17.4.

Final exam

0 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

реализирани активности 15.1 и 15.2

20.

Language of instruction

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature