Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
1AIN454Fundamentals of Cognitive Robotics3+0+03612.08.2025

 
Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program ARTIFICIAL INTELLIGENCE ENGINEERING
Type of Program Formal Education
Type of Course Unit Elective
Course Delivery Method Face To Face
Objectives of the Course To teach the basic concepts of cognitive robotic systems.
Course Content Kinematic models, sensors, vision and navigation
Course Methods and Techniques Lecture, problem solving
Prerequisites and co-requisities ( BBM102 ) and ( BBM104 )
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Özgür Erkent
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Hooman Samani, Cognitive Robotics, Taylor & Francis, 2016. Daniel Sebastian Leidner, Cognitive Reasoning for Compliant Robot Manipulation, Springer, 2019.
Course Notes Hooman Samani, Cognitive Robotics, Taylor & Francis, 2016.

Daniel Sebastian Leidner, Cognitive Reasoning for Compliant Robot Manipulation, Springer, 2019.


Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Midterm Exam 1 % 40
Final examination 1 % 60
Total
2
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 5 70
Preparation for Midterm Exam 1 20 20
General Exam Preparation 1 48 48
Total Work Load   Number of ECTS Credits 6 180

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Apply their knowledge of machine vision and robot kinematics to create computer programs that control mobile robots and robot arms, enabling the robots to recognize and manipulate objects and navigate their environments.
2 Explain how a robot can be designed to exhibit cognitive goal-directed behaviour through the integration of computer models of visual attention, reasoning, learning, prospection, and social interaction.
3  
4  
5  
6  
7  
8  

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to cognitive robotic systems
2 Development Environments: Gazebo, V-Rep, Matlab
3 Sensor and Actuator Models
4 Perception, Planning, Movement, Navigation
5 Manipulation
6 Manipulation
7 Language and communications
8 Language and communications
9 Social interactions
10 Social interactions
11 Locomotion
12 Locomotion
13 Neurorobotics
14 Haptics
15 Final exam preparation
16 Final exam

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
All 4 5 4 4 3 2 2 2 1 3 1 3
C1
C2
C3
C4
C5
C6
C7
C8

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
  https://bilsis.hacettepe.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=2733677&lang=en