Course syllabus adopted 2024-02-13 by Head of Programme (or corresponding).
Overview
- Swedish nameAutonoma robotar
- CodeTME290
- Credits7.5 Credits
- OwnerMPCAS
- Education cycleSecond-cycle
- Main field of studyEngineering Physics
- DepartmentMECHANICS AND MARITIME SCIENCES
- GradingTH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Course round 1
- Teaching language English
- Application code 11125
- Maximum participants48 (at least 10% of the seats are reserved for exchange students)
- Block schedule
- Open for exchange studentsYes
Credit distribution
Module | Sp1 | Sp2 | Sp3 | Sp4 | Summer | Not Sp | Examination dates |
|---|---|---|---|---|---|---|---|
| 0116 Examination 7.5 c Grading: TH | 7.5 c |
|
In programmes
- MPALG - COMPUTER SCIENCE - ALGORITHMS, LANGUAGES AND LOGIC, MSC PROGR, Year 1 (elective)
- MPCAS - COMPLEX ADAPTIVE SYSTEMS, MSC PROGR, Year 1 (compulsory elective)
- MPHPC - HIGH-PERFORMANCE COMPUTER SYSTEMS, MSC PROGR, Year 1 (elective)
- MPSYS - SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR, Year 1 (elective)
Examiner
Ola Benderius- Associate Professor, Vehicle Engineering and Autonomous Systems, Mechanics and Maritime Sciences
Eligibility
General entry requirements for Master's level (second cycle)Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.
Specific entry requirements
English 6 (or by other approved means with the equivalent proficiency level)Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.
Course specific prerequisites
Basic mathematical and programming skills are required. It is an advantage, but not absolutely necessary, to be familiar with modern C++ (version 11 or later) and Linux systems.Aim
The course aims at giving the students an understanding of design principles for autonomous systems, both robots and software agens, and also gives students the opportunity to apply their knowledge in practice through the construction of a simple autonomous robot.Learning outcomes (after completion of the course the student should be able to)
- Describe properties of common types of robotic hardware, including sensors, actuators, and computational nodes
- Apply modern software development and deployment strategies connected with autonomous robots
- Set up and use equations of motion of wheeled autonomous robots
- Apply basic sensor fusion
- Set up and use computer simulations of autonomous robots
- Apply global and local navigation of autonomous robots
- Apply the basics of behavior-based robotics
- Apply methods for decision making in autonomous robots
- Discuss the potential role of autonomous robots in society, including social, ethical, and legal aspects
- Discuss technical challenges with autonomous robots in society
Content
- Survey of robot related hardware
- Modern software development for autonomous robots
- Kinematics and dynamics for autonomous robots
- Simulation of autonomous robots
- Perception and sensor fusion for autonomous robots
- Behaviour modeling for autonomous robots
- Practical work related to autonomous robots
Organisation
- Lectures
- Home assignments (preparatory)
- Project including report and demonstration, groups of 2-4 students (mandatory)
- Exam (mandatory)
Literature
Lecture notes, scientific papers, and handouts. The material will be made available via the course web page.Examination including compulsory elements
- Exam (50%)
- Project (50%)
- Demonstration and report
- Oral examination of algorithmic design and engineering process
The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.