Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
1AIN451Introduction to 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 fundamental concepts of robotic systems.
Course Content This course is intended to present fundamentals of robotic systems. Specific subjects include: position and orientation in 3D space, manipulator forward and inverse kinematics, velocities and forces Jacobians relations, manipulator dynamics, stiffness and compliance control, trajectory control, mobile robots.
Course Methods and Techniques Interactive, discussion based learning, simulation, case study
Prerequisites and co-requisities ( BBM102 ) and ( BBM104 ) and ( AIN453 )
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Özgür Erkent
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Mark W. Spong, Seth Hutchinson, M. Vidyasagar, Robot Modeling and Control, John Wiley & Sons, Inc., 2006.
Course Notes Mark W. Spong, Seth Hutchinson, M. Vidyasagar, Robot Modeling and Control, John Wiley & Sons, Inc., 2006.


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 This course is designed to equip students with fundamental theories and computational methodologies that are used in design and analysis of robotic systems. Students will learn how to analytically formulate kinematic and dynamic equations for robot manipu
2 Rigid motions in space and homogeneous transformations, forward and inverse kinematics at configuration and velocity levels, and Lagrange's equations will be introduced. Computer-aided dynamic simulations with numerical time integration methods will be ex
3  
4  
5  
6  
7  
8  

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction
2 Rigid body motion and homogeneous transformations
3 Forward and inverse kinematics
4 Velocity kinematics and Jacobian
5 Velocity kinematics and Jacobian
6 Path and trajectory planning
7 Dynamics
8 Euler-Lagrange equations
9 State space theory
10 Independent joint control
11 Multivariable control
12 Force control
13 Geometric nonlinear control
14 Humanoid robots
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 5 3 2 1 1 2 1 1 1 2
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=2733675&lang=en