CENG0051 Fundamentals of Robot Autonomy

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code CENG0051
Name Fundamentals of Robot Autonomy
Term 2023-2024 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 Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Dr. Öğr. Üyesi Barış ATA


Course Goal / Objective

This course aims to provide a comprehensive understanding of the fundamental concepts and techniques involved in designing autonomous robots. By the end of the course, students will have gained a deep understanding of the principles and practices that underpin robot autonomy.

Course Content

This course covers the basics of robot autonomy, including robot perception and sensing, motion planning and control, and decision-making. Topics include robot sensors, state estimation, motion planning algorithms, control methods, and decision-making frameworks.

Course Precondition

Knowledge of basic programming, linear algebra, and probability theory.

Resources

Robotics: Modelling, Planning, and Control, by Bruno Siciliano and Lorenzo Sciavicco.

Notes

Probabilistic Robotics, by Sebastian Thrun, Wolfram Burgard, and Dieter Fox.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Understand the principles of robot autonomy and its applications.
LO02 Analyze perception systems for robots.
LO03 Implement control algorithms for robots.
LO04 Understand decision-making and planning for robots.


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 Autonomy Reading the lecture notes Öğretim Yöntemleri:
Anlatım
2 Robot Sensing and Perception Reading the lecture notes Öğretim Yöntemleri:
Anlatım
3 Robot Actuation and Control Reading the lecture notes Öğretim Yöntemleri:
Anlatım
4 Robotics and Computer Vision Reading the lecture notes Öğretim Yöntemleri:
Anlatım
5 Machine Learning Fundamentals Reading the lecture notes Öğretim Yöntemleri:
Anlatım
6 Perception and Learning in Robotics Reading the lecture notes Öğretim Yöntemleri:
Anlatım
7 Motion Planning and Navigation Reading the lecture notes Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Reading the lecture notes Ölçme Yöntemleri:
Yazılı Sınav
9 Multi-Robot Systems and Swarm Robotics Reading the lecture notes Öğretim Yöntemleri:
Anlatım
10 Robot Learning from Demonstration Reading the lecture notes Öğretim Yöntemleri:
Anlatım
11 Robot Perception and Mapping Reading the lecture notes Öğretim Yöntemleri:
Anlatım
12 Robot Control in Dynamic Environments Reading the lecture notes Öğretim Yöntemleri:
Anlatım
13 Human-Robot Interaction and Collaborative Robotics Reading the lecture notes Öğretim Yöntemleri:
Anlatım
14 Robot Planning and Decision Making 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

Update Time: 23.05.2023 12:30