BÄ°L755 - ROBOTICS

Course Name Code Semester Theory
(hours/week)
Application
(hours/week)
Credit ECTS
ROBOTICS BÄ°L755 Any Semester/Year 3 0 3 8
PrequisitesNone.
Course languageTurkish
Course typeElective 
Mode of DeliveryFace-to-Face 
Learning and teaching strategiesLecture
Preparing and/or Presenting Reports
Problem Solving
Project Design/Management
 
Instructor (s)Department Responsible (bbm-bologna@cs.hacettepe.edu.tr) 
Course objectiveThis course presents the principal robotics architecture and applications.  
Learning outcomes
  1. After completing the course, the students will gain a deep understanding about fundamental topics in robotics
Course ContentIntroduction to Robotics
Theory of robotics control
Kinematic and inverse kinematics
Actuators
Robot Controls and environments
Mobile Robots
Localizations
 
ReferencesBruno Siciliano, Lorenzo Sciavicco, Luigi Villani , Giuseppe Oriolo, Robotics: Modelling, Planning and Control (Advanced Textbooks in Control and Signal Processing) , Springer; February 11, 2011ISBN 978-1846286414
Reza N. Jazar, Theory of Applied Robotics: Kinematics, Dynamics, and Control, Springer; 2nd ed. edition (June 21, 2010), ISBN-13: 978-1441917492
Dario Floreano, Jean-Christophe Zufferey, Mandyam V. Srinivasan, Charlie Ellington, Flying Insects and Robots, Springer;(December 3, 2009) ISBN-13: 978-3540893929 

Course outline weekly

WeeksTopics
Week 1Introduction to Robotics
Week 2Theory of robotics control
Week 3Theory of robotics control (cont?d.)
Week 4Kinematic and inverse kinematics
Week 5Kinematic and inverse kinematics (cont?d.)
Week 6Actuators
Week 7Actuators (cont?d.)
Week 8Robot Controls and environments
Week 9Robot Controls and environments (cont?d.)
Week 10Mobile Robots
Week 11Mobile Robots (cont?d.)
Week 12Localizations
Week 13Localizations (cont?d.)
Week 14Project presentations
Week 15Final exam study
Week 16Final Exam

Assesment methods

Course activitiesNumberPercentage
Attendance00
Laboratory00
Application00
Field activities00
Specific practical training00
Assignments315
Presentation00
Project130
Seminar00
Midterms00
Final exam150
Total95
Percentage of semester activities contributing grade succes050
Percentage of final exam contributing grade succes050
Total100

WORKLOAD AND ECTS CALCULATION

Activities Number Duration (hour) Total Work Load
Course Duration (x14) 14 3 42
Laboratory 0 0 0
Application000
Specific practical training000
Field activities000
Study Hours Out of Class (Preliminary work, reinforcement, ect)14228
Presentation / Seminar Preparation000
Project1102102
Homework assignment31442
Midterms (Study duration)000
Final Exam (Study duration) 12626
Total Workload33147240

Matrix Of The Course Learning Outcomes Versus Program Outcomes

D.9. Key Learning OutcomesContrubition level*
12345
1. Graduates should have a mastery of computer science as described by the core of the Body of Knowledge.   X 
2. Graduates need understanding of a number of recurring themes, such as abstraction, complexity, and evolutionary change, and a set of general principles, such as sharing a common resource, security, and concurrency.   X  
3. Graduates of a computer science program need to understand how theory and practice influence each other.    X
4. Graduates need to think at multiple levels of detail and abstraction.  X   
5. Students will be able to think critically, creatively and identify problems in their research.    X
6. Graduates should have been involved in at least one substantial project.     X
7. Graduates should realize that the computing field advances at a rapid pace.     X
8. Graduates should conduct research in an ethical and responsible manner.   X  
9. Graduates should have good command of technical terms in both Turkish and English.    X
10. Graduates should understand the full range of opportunities available in computing.   X 
11. Graduates should understand that computing interacts with many different domains.     X
12. Graduates should develop the knowledge acquired at master level and apply scientific methods in order to solve scientific problems.     X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest