Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
1AIN453Robotics Laboratory0+2+01412.08.2025

 
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 introduce the basic robotic system components and to experimentally validate the modeling and control systems.
Course Content This course aims to teach the basics of robotic systems with experimental methods. Topics include: Coordinate transformations, deriving kinematic relations, Denavit-Hartenberg notation, obtaining a dynamic model, controller design, validation and controller tuning.
Course Methods and Techniques Experimental work
Prerequisites and co-requisities ( BBM102 ) and ( BBM104 ) and ( AIN451 )
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
Laboratory Work 14 % 60
Final examination 1 % 40
Total
15
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Hours for off-the-c.r.stud 14 3 42
Laboratory 14 2 28
General Exam Preparation 1 30 30
Total Work Load   Number of ECTS Credits 3,33333333333333 100

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Application of existing analytical approaches to modeling and control of robotic systems and gaining the ability of experimental validation. Upon successful completion of this course, students will be able to design position, velocity and force control in
2  
3  
4  
5  
6  
7  
8  

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Experiment 0: Lab Rules
2 Experiment 1: Rigid body motion and homogeneous transformations
3 Experiment 2: Forward and inverse kinematics
4 Experiment 3: Velocity kinematics and Jacobian (simulation)
5 Experiment 4: Velocity kinematics and Jacobian
6 Experiment 5: Path and trajectory planning
7 Experiment 6: Dynamical modeling
8 Experiment 7: Model validation
9 Experiment 8: State space model validation
10 Experiment 9: Independent joint control
11 Experiment 10: Multivariable control
12 Experiment 11: Force control
13 Experiment 12: Nonlinear control
14 Experiment 13: Humanoid/mobile 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 5 5 5 4 4 3 3 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=2733676&lang=en