Computer Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Computer Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Computer Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 05081908 | Mobile Robots | 4 | Spring | 8 | 3+0+0 | 3 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | Yok |
| Mode of Delivery | Face to Face |
| Prerequisites | Yok |
| Coordinator | - |
| Instructor(s) | Asst. Prof. Ali Osman ÇIBIKDİKEN |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Ali Osman ÇIBIKDİKEN | A-124 | [email protected] | 7585 | Monday 14.00-15.00 |
Course Content
The content of the course is selected from robotic manipulators, mobile robots, land vehicles, rotary wing helicopters, fixed-wing aircraft, underwater vehicles and underwater vehicles. Using Newton-Euler and Lagrange methods, nonlinear model extraction, inertial measurement systems, estimation of state variables by Kalman filter, and linear and nonlinear control techniques are applied to autonomous vehicles. Students are expected to prepare and present their term projects with technical documentation software. It is encouraged to use Matlab / Simulink software effectively and to create virtual reality environments in projects.
Objectives of the Course
This course aims to examine current trends and developments in modeling, simulation and control of autonomous robots.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | |
| Support Courses | X |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P2 | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose | 5 |
| P3 | Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose | 2 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Knowledge of algorithm design and analysis techniques. | P.3.1 | 1 |
| O2 | Must know the concepts of state variables and state model in electrical-electronic systems. | P.3.8 | 2 |
| O3 | Can write user interface programs for electronic systems | P.3.15 | 1 |
| O4 | Data analysis | P.2.22 | 1 |
| O5 | To analyze digital and analog signal analysis. | P.2.26 | 7 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | In-class leaflets |
| 2 | Stability analysis |
| 3 | Kinematics and Dynamics of Robots |
| 4 | Artificial intelligence control architectures |
| 5 | Control of robots with artificial intelligence |
| 6 | Kinematics and dynamics of land vehicles |
| 7 | Autonomous control of land vehicles |
| 8 | Rotary vane vehicle modeling |
| 9 | Midterm Exam 1 |
| 10 | Autonomous control of rotary wing aircraft |
| 11 | Kinematics and dynamics of fixed-wing aircraft |
| 12 | Autonomous control of fixed-wing aircraft |
| 13 | Kalman filter |
| 14 | INS and GPS integration |
| 15 | Final |
Textbook or Material
| Resources | George A. Bekey, Autonomous Robots: From Biological Inspiration to Implementation and Control, The MIT Press, 2005. |
| George A. Bekey, Autonomous Robots: From Biological Inspiration to Implementation and Control, The MIT Press, 2005. |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Quiz | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 4 | 56 |
| Midterms | 1 | 3 | 3 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 3 | 3 |
| Other | 14 | 4 | 56 |
| Total Work Load: | 160 | ||
| Total Work Load / 30 | 5,33 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P2 | P3 |
|---|---|---|---|
| O1 | Data analysis | 3 | - |
| O2 | To analyze digital and analog signal analysis. | - | 5 |
| O3 | Knowledge of algorithm design and analysis techniques. | 1 | 3 |
| O4 | Must know the concepts of state variables and state model in electrical-electronic systems. | 4 | - |
| O5 | Can write user interface programs for electronic systems | - | 2 |