Course syllabus

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TME290 / FIM764 Autonomous robots - lp4 (7.5 hp)

The course is offered by the department of Mechanics and Maritime Sciences.

Contact details

Please contact the course staff for any further questions about the teaching or course subjects. If a meeting is required, please make contact by email to request an appointment (during office hours).

Examiner and lecturer

Ola Benderius, 031-772 2086, ola.benderius@chalmers.se

Course assistants

Krister Blanch, krister.blanch@chalmers.se

Tarun Kadri Sathiyan, tarun.sathiyan@chalmers.se

Study administrator

Per Thorén, thoren@chalmers.se

Course purpose

The course aims at giving the students an understanding of design principles for autonomous systems, both robots and software agents, and also gives students the opportunity to apply their knowledge in practice through the construction of an industry-relevant autonomous robot.

Course design

The course consist of lectures and lab work. In the lectures the main theories of autonomous robots are covered, which will provide the students with a broad overview of the subject area. Furthermore, the students are expected to apply the knowledge from the lectures in the lab work by solving a set of predefined tasks.

The lab work consist of computer simulations and hardware sessions with supervision by teachers, targeting a final robot demonstration as a goal. The students are expected to carry out some project work outside class hours. The projects should be carried out in teams of 3–4 students per group. The project needs to be passed in order to pass the course.

The final grade of the course is given by an individual written exam.

Lab sessions will partly take place in the Robotics lab located in the M-building. The lab is located next to the Chalmers wind tunnel. Time slots for the lab are bookable online.

Schedule

TimeEdit

Lectures:

Tue 25/3 13:15-15:00 ED Lecture 1: Introduction and autonomous robots in society
Thu 27/3 13:15-15:00 ED Lecture 2: Robot hardware basics and software engineering for robots
Fri 28/3 13:15-15:00 ED Lecture 3: OpenDLV and microservices for robots
Tue 1/4 13:15-15:00 EE Lecture 4: Modular simulation of differentially steered robots
Tue  8/4 13:15-15:00 ED Lecture 5: Data replay and development of robot vision algorithms
Thu 10/4 13:15-15:00 ED Lecture 6: Local control and global navigation
Fri 11/4 13:15-15:00 ED Lecture 7: Sensor fusion and SLAM
EASTER
Thu 24/4 13:15-15:00 ED Lecture 8: The Kiwi D1 robot and advanced robot testing with HIL
Fri 25/4 13:15-15:00 ED Lecture 9: Decision making using BBR, ANN, and ER (with guest lecture from previous students)
Tue 29/4 13:15-15:00 ED Lecture 10: Summary
Wed 21/5 10:00-15:00 ML11 Lab demonstrations
Tue 27/5 15:15-17:00 ML13 Exam Q&A

Course literature

Lecture notes, source code templates, and web links. The material will be made available via the course web page.

Learning objectives and syllabus

  • 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

Examination form

The examination consists of a written exam. The lab part needs to be approved in order to pass the course.

See the following subsections for details regarding assessment and grading. Refer also to the below section regarding plagiarism.

Grades

The grades that are given in this course are the following: 5, 4, 3, U (not passed).

Written exam

The written exam will be graded U, 3, 4, or 5. A minimum grade of 3 is required in order to pass the course. The exam will cover all lectures, as well as key components from the lab work.

Regarding plagiarism

Briefly, plagiarism occurs when someone present ideas, concepts, texts, or other structures from someone else, as their own. I.e. without appropriately acknowledging the original source. See further in the document about Academic integrity and honesty at Chalmers (link).

Note: All suspected cases of plagiarism will be reported to the university disciplinary committee (disciplinnämnden)!

Course summary:

Date Details Due