• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. Each student contributes to the development of writing ability by writing a report in a paper format within the scope of the project.

   Contribution to Program Outcomes

   1. To be able to express ideas and findings related to the research topic both orally and in writing.
   2. Demonstrating professional and ethical responsibility.

   Method of assessment

   1. Written exam
   2. Homework assignment
   3. Seminar/presentation
   4. Term paper
2. Upon completing the course, students will have a solid understanding of the foundational theories behind autonomous mobile robots, including kinematics, path planning, localization, sensor fusion, and control. They will be able to analyze and evaluate algorithms for autonomous navigation and real-time decision-making in dynamic environments.

   Contribution to Program Outcomes

   1. To gain in-depth knowledge about the sensor systems utilized in military applications.
   2. To gain insight and experience about the solution approaches to the technical problems encountered in projects.
   3. To enroll in and contribute to the R&D projects.
   4. Find out new ways to improve current knowledge
   5. To understand the basic principles and applications of new tools and / or software required for thesis work.

   Method of assessment

   1. Written exam
   2. Homework assignment
   3. Seminar/presentation
   4. Term paper
3. Students will gain hands-on experience in designing and implementing these concepts using robotic frameworks, such as the Robot Operating System (ROS). They will apply theoretical knowledge to build and test autonomous mobile robots, focusing on practical skills in navigation, sensor integration, and system control.

   Contribution to Program Outcomes

   1. To gain in-depth knowledge about the sensor systems utilized in military applications.
   2. To enroll in and contribute to the R&D projects.
   3. Work effectively in multidisciplinary research teams.
   4. To be able to express ideas and findings related to the research topic both orally and in writing.
   5. Be aware of the importance of nanoscience and nanoengineering in understanding the working principles of the new generation nano devices.

   Method of assessment

   1. Written exam
   2. Homework assignment
   3. Seminar/presentation
   4. Term paper

Contents
Week 1:	Explanation of concepts in mobile robotics.
Week 2:	Kinematics of mobile robots and linear motion equations.
Week 3:	Kinematics of mobile robots and nonlinear motion equations.
Week 4:	Sensors in mobile robots and measurement equations.
Week 5:	Sensors and nonlinear measurement equations in mobile robots. Sensor fusion.
Week 6:	Control applications and actuators in mobile robots.
Week 7:	Path planning in discrete space.
Week 8:	Path planning in continuous space.
Week 9:	Path tracking and uncertainty.
Week 10:	Centralized sensor fusion.
Week 11:	Path planning in autonomous swarms.
Week 12:	Distributed sensor fusion in swarms.
Week 13:	Introduction to Robot Operating System (ROS)
Week 14:	Introduction to Robot Operating System (ROS).
Week 15*:	-
Week 16*:	-
Textbooks and materials:
Recommended readings:	Mobile Robot: Navigation, Control and Remote Sensing by Gerald Cook, John Wiley & Sons, 2011. Principles of Robot Motion: Theory, Algorithms, and Implementation by Howie Choset, MIT press, 2005 Introduction to Autonomous Mobile Robots by Roland Siegwart, MIT press, 2011. Introduction to Mobile Robot Control by Spyros G. Tzafestas, Elsevier, 2014.
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:		0
Other in-term studies:		0
Project:	1	50
Homework:		0
Quiz:		0
Final exam:	14	50
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	16
Own studies outside class:	4	16
Practice, Recitation:	0	0
Homework:	0	0
Term project:	1	1
Term project presentation:	2	2
Quiz:	0	0
Own study for mid-term exam:	4	8
Mid-term:	2	1
Personal studies for final exam:	4	8
Final exam:	2	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)