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Course Description Course Name : Intelligent Robotics I Course Code : EE-703 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. CABBAR VEYSELBAYSAL Learning Outcomes of the Course : Knows basic components of robotic systems Knows robot kinematics and inverse kinematics Knows robot dynamics and force control Knows sensors and sensor fusion Knows robot control architectures Robot learning Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : Main objective of the "Intelligent Robotics" course is to teach the advanced methods (state-of the art) which are needed to design and produce autonomous , flexible , dexterous and intelligent robots, including use of the methods in various applications. It is the first half of a two semester course. Course Contents : Introduction. Basic components of robotic systems, robot kinematics, robot dynamics and force control, sensor fusion, robot control architectures and behavior based reasoning, intelligent control techniques for task and motion control and robot learning. Language of Instruction : English Work Place : Graduate Lecture Room of the EE Dept.   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction to robotics Study of Lecture Materials Lecture in Classroom 2 Basic components of robotic systems Study of Lecture Materials Lecture in Classroom 3 Forward and inverse kinematics for robots Study of Lecture Materials Lecture in Classroom 4 Forward and inverse kinematics for robots Study of Lecture Materials Lecture in Classroom 5 Dynamics of robots and force control Study of Lecture Materials Lecture in Classroom 6 Dynamics of robots and force control Study of Lecture Materials Lecture in Classroom 7 Environment monitoring, sensing and sensor fusion Study of Lecture Materials Lecture in Classroom 8 Environment monitoring, sensing and sensor fusion Study of Lecture Materials Lecture in Classroom 9 Midterm Exam Study of Lecture Materials for Exam Written Exam, 10 Robot control architectures and behavior based reasoning Study of Lecture Materials Lecture in Classroom 11 Robot control architectures and behavior based reasoning Study of Lecture Materials Lecture in Classroom 12 Intelligent control methods for robot task and motion control Study of Lecture Materials Lecture in Classroom 13 Intelligent control methods for robot task and motion control Study of Lecture Materials Lecture in Classroom 14 Robot learning Study of Lecture Materials Lecture in Classroom 15 Robot learning Study of Lecture Materials Lecture in Classroom 16/17 Student Project Presentations Project preparation Presentation in Classroom   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Lecture Notes   Arkin R.,”Behavior Based Robotics”,MIT Press.,1998.  Bekey G., “Autonomous Robots”, MIT Press.,2005 Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 50     Homeworks/Projects/Others 4 50 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Communicates with people in an appropriate language and style. 1 2 Specializes by furthering his knowledge level at least in one of the basic subfields of electiral-electronic engineering. 4 3 Grasps the integrity formed by the topics involved in the field of specialization. 4 4 Grasps and follows the existing literature in the field of specialization. 5 5 Comprehends the interdisciplinary interaction of his field with other fields. 5 6 Has the aptitude to pursue theoretical and experimental work. 3 7 Forms a scientific text by compiling the knowledge obtained from research. 3 8 Works in a programmed manner within the framework set by the advisor on the thesis topic, in accordance with the logical integrity required by this topic. 3 9 Performs a literature search in scientific databases; in particular, to scan the databases in an appropriate manner, to list and categorize the listed items. 4 10 Has English capability at a level adequate to read and understand a scientific text in his field of specialization, written in English. 4 11 Compiles his/her knowledge in his/her field of specialization. in a presentation format, and presents in a clear and effective way. 3 12 Writes a computer code aimed at a specific purpose, in general, and related with his/her field of specialization, in particular 3 13 Pursues research ın new topics based on his/her existing research experıence. 3 14 Gives guidance in environments where problems related with his/her field need to be solved, and takes initiative. 3 15 Develops and evaluates projects, policies and processes in his field of specialization. 2 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 3 42 Assesment Related Works     Homeworks, Projects, Others 4 15 60     Mid-term Exams (Written, Oral, etc.) 1 6 6     Final Exam 1 6 6 Total Workload: 156 Total Workload / 25 (h): 6.24 ECTS Credit: 6