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| MAKL7532 | Autonomous Mobile Robots | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | DEPARTMENT of MECHANICAL ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Lab work | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Doç. Dr. Nurhan GÜRSEL ÖZMEN | | Co-Lecturer | | | Language of instruction | | | Professional practise ( internship ) | None | | | | The aim of the course: | | To learn the fundemantals of mobile robotics
To learn the mechenical and electrical properties of mobile robots
To design and control a mobile robot
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| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | will be able to gain the ability to apply engineering problems for modeling and solving. | 1,2 | 1,6, | | PO - 2 : | Will be able to gain the ability to select and apply appropriate analysis and modeling methods to complex engineering problems related to mechanical engineering. | 1,2 | 1,6, | | PO - 3 : | Will be able to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions. | 1,2 | 1,6, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| *Locomotion, Legged mobile robots and wheeled mobile robots
*Mobile Robot Kinematics, Kinematic models and constraints, mobile robot maneuverability
*Perception,sensors for mobile robots, feature extraction
*Mobile robot localization,noise and aliasing, examples of localization systems
* Planning and navigation, path planning, obstacle avoidance
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to mobile robots
An overview of the course and the references | | | Week 2 | -Locomotion
-Key issues for locomotion
-Legged mobile robots | | | Week 3 | -Wheeled mobile robots
-Wheeled locomotion: the design space | | | Week 4 | Mobile robot kinematics
-Kinemtic models and constraints | | | Week 5 | Mobile robot maneuverability
-Degree of mobility
-Degree of steerability
-Robot maneuverability | | | Week 6 | Mobile robot workspace
-Degrees of freedom
-Holonomic robots
-Path and trajectory considerations | | | Week 7 | Perception
-Sensors for mobile robots
-Sensor classifications
-Uncertainity
| | | Week 8 | Feature extraction
-Feature extraction based on range data
-Visual appearance based feature extraction | | | Week 9 | First axam | | | Week 10 | Mobile robot localization
-The challenge of localization: Noise and aliasing
-Sensor noise, sensor aliasing | | | Week 11 | Localization based navigation | | | Week 12 | Map representation | | | Week 13 | Probabilistic based map representation | | | Week 14 | -Other examples of localization systems | | | Week 15 | Planning and navigation | | | Week 16 | Project presentation | | | |
| 1 | Siegwart,R., Nourbabakhsh, I.R., Scaramuzza,D., 2010,Introduction to Autonomous Mobile Robots, the MIT Press | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 20.5.2022 | 2 | 50 | | Project | 12-14 | 20.6.2022 | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 10 | 30 | | Sınıf dışı çalışma | 3 | 10 | 30 | | Laboratuar çalışması | 2 | 10 | 20 | | Arasınav için hazırlık | 10 | 1 | 10 | | Arasınav | 2 | 1 | 2 | | Proje | 20 | 6 | 120 | | Total work load | | | 212 |
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