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Information
| Code | CENG0055 |
| Name | Advanced Robot Motion Planning and Control |
| Term | 2024-2025 Academic Year |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi Barış ATA |
Course Goal / Objective
This course aims to introduce students to advanced topics in robot motion planning and control. The course will enable students to develop an in-depth understanding of robot motion planning and control, which is essential for designing complex robotic systems.
Course Content
The course covers advanced algorithms and techniques for robot motion planning, including trajectory generation, optimization-based planning, sampling-based planning, and motion planning under uncertainty. The course also covers advanced topics in robot control, including feedback control, force control, impedance control, and adaptive control.
Course Precondition
Undergraduate-level courses in robotics, mathematics, and computer science
Resources
"Robot Motion Planning and Control" by Steven M. LaValle
Notes
Research papers and articles on advanced topics in robot motion planning and control
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Understand the fundamental principles of robot kinematics and dynamics |
| LO02 | Analyze and design feedback control systems for robots |
| LO03 | Apply force control techniques to manipulate objects |
| LO04 | Apply nonlinear control techniques to manipulate objects |
| LO05 | Apply adaptive control techniques to manipulate objects |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering. | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. | 3 |
| PLO03 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the new and developing practices of his / her profession and examining and learning when necessary. | 2 |
| PLO04 | Yetkinlikler - Öğrenme Yetkinliği | Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. | 2 |
| PLO05 | Yetkinlikler - Öğrenme Yetkinliği | Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. | 4 |
| PLO06 | Yetkinlikler - Öğrenme Yetkinliği | Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. | |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Has the skills of learning. | 2 |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary. | 1 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering. | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. | 1 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. | 2 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Observes social, scientific and ethical values in all professional activities. | 2 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to Robot Motion Planning and Control | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 2 | Kinematics and Dynamics of Robots | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 3 | Feedback Control | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 4 | Force Control | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 5 | Trajectory Generation | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 6 | Optimization-based Planning | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 7 | Sampling-based Planning | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Reading the lecture notes | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Motion Planning in Complex Environments | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 10 | Hybrid Planning and Control | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 11 | Nonlinear Control | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 12 | Adaptive Control | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 13 | Reinforcement Learning for Robotics I | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 14 | Reinforcement Learning for Robotics II | Reading the lecture notes | Öğretim Yöntemleri: Anlatım |
| 15 | Review | Reading the lecture notes | Öğretim Yöntemleri: Soru-Cevap |
| 16 | Term Exams | Reading the lecture notes | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | Reading the lecture notes | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 14 | 14 |
| Final Exam | 1 | 28 | 28 |
| Total Workload (Hour) | 154 | ||
| Total Workload / 25 (h) | 6,16 | ||
| ECTS | 6 ECTS | ||