The course covers fundamental problems of autonomous mobile robotics including locomotion, reception, localization, planning and navigation. In the context of locomotion, legged, wheeled, flying and swimming mobile robots will be discussed. In the reception part, various sensors that are used on mobile robots will be introduced and several sensor fusion algorithms will be presented. Localization problems will be tackled in a probabilistic framework using Markov and Kalman Filtering techniques. Simultaneous Localization and Mapping (SLAM) problem and its variations will also be introduced and discussed. Finally planning and navigation strategies will be covered.
Autonomous Mobile Robotics (ME 525)
2022 Fall
Faculty of Engineering and Natural Sciences
Mechatronics(ME)
3
10.00
Kemalettin Erbatur erbatur@sabanciuniv.edu,
Click here to view.
English
Doctoral, Master
--
Formal lecture,Laboratory
Click
here
to view.
| Programs\Type | Required | Core Elective | Area Elective |
| MA-European Studies | |||
| MA-European Studies-Non Thesis | |||
| MA-Political Science | |||
| MA-Political Science-Non Thes | |||
| MA-Visual Arts&Vis. Com Des-NT | |||
| MA-Visual Arts&Visual Com Des | |||
| MS-Bio. Sci. & Bioeng. LFI | |||
| MS-Bio. Sci. & Bioeng. LFI-ENG | |||
| MS-Biological Sci&Bioeng. | * | ||
| MS-Computer Sci.&Eng. LFI | |||
| MS-Computer Sci.&Eng. LFI-ENG | |||
| MS-Computer Science and Eng. | * | ||
| MS-Cyber Security(with thesis) | * | ||
| MS-Data Science | |||
| MS-Elec. Eng&Comp Sc.LFI-ENG | |||
| MS-Electronics Eng&Comp Sc.LFI | |||
| MS-Electronics Eng&Computer Sc | * | ||
| MS-Electronics Eng. | * | ||
| MS-Electronics Eng. LFI | |||
| MS-Electronics Eng. LFI-ENG | |||
| MS-Energy Techno.&Man. | * | ||
| MS-Industrial Eng. LFI-ENG | |||
| MS-Industrial Engineering | * | ||
| MS-Industrial Engineering LFI | |||
| MS-Manufacturing Eng-Non Thes | * | ||
| MS-Manufacturing Engineering | * | ||
| MS-Materials Sci & Engineering | * | ||
| MS-Materials Sci. & Eng. LFI | |||
| MS-Materials Sci.&Eng. LFI-ENG | |||
| MS-Mathematics | |||
| MS-Mechatronics | * | ||
| MS-Mechatronics LFI | |||
| MS-Mechatronics LFI-ENG | |||
| MS-Physics | |||
| MS-Physics-Non Thesis | * | ||
| MS-Psychology | |||
| MS-Psychology-Non Thesis | |||
| PHD-Biological Sci&Bioeng. | * | ||
| PHD-Comp. Sci and Eng.after UG | * | ||
| PHD-Computer Science and Eng. | * | ||
| PHD-Cyber Security | * | ||
| PHD-Electronics Eng&ComputerSc | * | ||
| PHD-Electronics Eng. | * | ||
| PHD-Electronics Eng. after UG | * | ||
| PHD-Experimental Psychology | |||
| PHD-Industrial Engineering | * | ||
| PHD-Management | |||
| PHD-Manufacturing Eng after UG | * | ||
| PHD-Manufacturing Engineering | * | ||
| PHD-Materials Sci.&Engineering | * | ||
| PHD-Mathematics | |||
| PHD-Mechatronics | * | ||
| PHD-Mechatronics after UG | * | ||
| PHD-Physics | |||
| PHD-Physics after UG | |||
| PHD-Social Psychology | |||
| PHDBIO after UG | * | ||
| PHDCYSEC after UG | * | ||
| PHDEECS after UG | * | ||
| PHDEPSY after UG | |||
| PHDIE after UG | * | ||
| PHDMAN after UG | |||
| PHDMAN after UG-Finance | |||
| PHDMAN after UG-Man. and Org. | |||
| PHDMAN after UG-Op.&Sup. Cha. | |||
| PHDMAN-Finance Area | |||
| PHDMAN-Man. and Org. Area | |||
| PHDMAN-Op. & Supp. Chain Area | |||
| PHDMAT after UG | * | ||
| PHDMATH after UG | |||
| PHDSPSY after UG |
CONTENT
OBJECTIVE
To teach fundamentals of autonomous mobile robotics that include locomotion, perception, localization, mapping, planning and navigation of mobile robots so that students can acquire a solid theoretical background and hands-on experience in mobile robotics.
LEARNING OUTCOME
After taking this course, students should be able to:
- evaluate various locomotion mechanisms including legged, wheeled and flying locomotions.
- analyze motion kinematics of non-holonomic wheeled mobile robots
- quantify mobility and maneuverability of wheeled robots
- design feedback controllers for motion control of the wheeled mobile robots
- select appropriate sensors for perception including non-visual and visual sensors
- implement localization algorithms using Markov and Kalman filter
- Implement simple SLAM algorithms using Extended Kalman Filter (EKF)
- Synthesize optimal paths using artificial potential functions
- demonstrate hands on experience with Lego Mindstorm EV3 robots
Update Date:
ASSESSMENT METHODS and CRITERIA
| Percentage (%) | |
| Final | 30 |
| Midterm | 20 |
| Exam | 3 |
| Assignment | 22 |
| Participation | 5 |
| Homework | 20 |
RECOMENDED or REQUIRED READINGS
| Textbook |
Introduction to Autonomous Mobile Robots, 2nd Edition, Roland Siegwart, Illah R. Nourbakhsh and Davide Scaramuzza, MIT Press, 2011. |
| Readings |
- Computational Principles of Mobile Robotics, Gregory Dudek, Michael Jenkin, Cambridge University Press, 2010. - Autonomous Robots, George A. Bekey, MIT Press, 2005. |