Introduction to Robotics

Faculty: Faculty of Engineering
Department(s): All faculty (CIV, CE, IE, EE, IM)
Number of Students:
Course: Introduction to Robotics
Weekly hours: Theory: 2 Exercises: 0
ECTS Credits: 4
Semester: Fall

Lecture Schedules:

Classroom: B-306 (computer lab) - temporary for any changes you will be informed in the classroom.

Day/time: Friday; 9:15AM - 11:00AM

Lecturer: Dr. Hiqmet Kamberaj
Room Number: —-
Phone Number of the lecturer:
E-mail address of the lecturer: km.ude.ubi|jarebmakh#km.ude.ubi|jarebmakh

Course Objectives:

In this course, we aim to give an introduction to the elements of the robotics. The students will be able to learn about the robotics and their applications; Sensors; Reactive behavior; Finite state machines; Robotic motion and odometry; Control; Local navigations; Localization; Mapping and Mapping-based navigation; Fuzzy logic control; Image processing; Neural networks; Machine learning; Swarm robotics; Kinematics of a robotic manipulator.

Learning Outcomes:

Skill outcomes Necessary ( + ) Not Necessary ( –)
Written communication skills +
Oral communication skills +
Computer skills +
Working in laboratory +
Working team +
Preparing projects +
Knowledge of foreign language (English) +
Scientific and professional literature analysis +
Problem solving skills +
Management skills +
Presentation skills +

Course Textbooks:

  1. H. Kamberaj, Lecture Notes in Robotics, 2022.

Teaching methods:

Teaching methods Ideal %
Teaching ex cathedra (teacher as the figure of authority, standing in front of the class and lecturing) 70
Interactive teaching (ask questions in class, assign and check homework, or hold class or group discussions) 20
Mentor teaching (consultant-teacher who has a supervisory responsibility and supervising the students) -
Laboratory work -
Seminar work 5
Field Work (enables students to examine the theories and the practical experiences of a particular discipline interact) -
Semester project -
Case Study (An in-depth exploration of a particular context) -
Students Teamwork 5


  • Students are obliged to attend at least 72 % out of 12 weeks of lectures, exercises, and other activities.
  • The attendance rule for failed overlapping courses is 36 % out of 12 weeks of lectures, exercises, and other activities.
  • The attendance rule for course from the upper semester is 57% out of 12 weeks of lectures, exercises, and other activities.
  • Students are not obliged to attend the course if the course is double repeated. However, they need to register the course.

Exams (Mid-Term Exam, Final Exam, Make-up Exam):

There are two exams, the Mid-Term and Final Exam, at the middle and at the end of the semester, respectively. The students, who do not earn minimum 50 credit points from the Mid-Term, Final Exam including Homework Assignments, have to take the Make-Up Exam, which counts only for Final Exam credit points. The terms of the exams are defined by the Academic Calendar announced on the University web site.

Passing Score:

The maximum number of credit points is collected during the semester, as follows: Mid-term Exam = 40 Credit Points (minimum requirement is 25 % (midterm exam + activity) to enter Final Exam), Final Exam (minimum requirement is 25 % to pass) = 40 Credit Points. Homeworks, quizzes, specific assignments and term papers = 20 Credit Points. Total=100.

Study Plan —- International Balkan University - Academic Calendar

~Week Lecture ~ Topics
1 1 Introduction to the philosophy of this course. Robotics and their Applications.
2 2 Sensors. Reactive behavior.
3 3 Finite state machines. Robotic Motion and Odometry.
4 4 Control. Local Navigation and Localization.
5 5 Mapping and Mapping-based Navigation.
6 6 Midterm review.
7 - Mid Term Exam Week
8 7 Fuzzy logic control.
9 8 Image processing.
10 9 Neural Networks and Machine Learning.
11 10 Swarm robotics.
12 11 Kinematics and a robotic manipulator.
13 12 Final exam review.
14 - Winter break.
15 - Final exam week.
16 - Preparatory week.
17 - Make up exam week.

Student workload:

For calculating the Total Student Work Load we multiply the course ECTS credits with standard figure 30. (ECTS Credit: 4) x 30 = 120 hours.

Activities Hours
Lecture hours for 12 weeks: 24
Laboratory and class exercises for 12 weeks: -
Student Mentoring for 12 weeks: 10
Consultation for 12 weeks: 10
Exam preparations and exam hours (Midterm, final, Makeups): 36
Individual reading work for 12 weeks (Reading assignments/expectations for reading and comprehension is 5 pages per hour. Example: If a book 300 pages, total Individual reading work for 12weeks 300:5 = 60 hours. 20
Homework and work practice for 12 weeks: 20
Preparation of diploma work, for 12 weeks: -
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