Course syllabus

Special instructions due to Covid19

The course will be run remotely due to the pandemic. There will be an non-mandatory possibility to connect your groups DevOps engineering process to a course robot in order to evaluate your solution. Note: There will be no scheduled lab sessions or work at campus.

For the scheduled lecture times, we will use Zoom to answer questions and discuss the material that I will send out in advance as video lectures. An exception will be the first lecture on March 23 where I will give the lecture live over Zoom. For all teaching activities in this course we will use my private Zoom room at https://zoom.us/my/benderius, if nothing else have been decided.

The Canvas Discussion pages will be used extensively to give guidance and hints for the home problems and the project work, as well as for Peer-assisted learning (PAL). Please log in to Canvas several times per week to keep you updated on the discussions, and try your best to take part!

Course-PM

TME290 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

Björnborg Nguyen, bjornborg.nguyen@chalmers.se

Study administrator

Bengt-Erik Mellander, 031-772 3340, f5xrk@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 a industry-relevant autonomous robot.

Schedule

TimeEdit

Course literature

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

Course design

The course consist of lectures, home problems, and a project. 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 project and in the home problems.

The project part of the course consist of lab sessions with supervision by teachers, targeting a final robot demonstration as a goal, including several sub-goals. 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.

Moreover, there are mandatory home problems that has to be carried out individually by each student. Both the project part and the individual homework part contribute to the student’s final grade on the course. Please read further details regarding assessment and grading below.

Lab sessions will take place in the Robotics lab located in the Mechanical Engineering building, and the time slots in the lab are bookable during the course.

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 and evolutionary 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

Link to the syllabus on Studieportalen.

Study plan

Examination form

The examination consists of graded individual homework assignments and a graded project. Both the results on the individual homework part as well as the project group work results contribute to the student’s final grade on the course. There is also a final individual assessment meeting in the end of the course, see below.

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).

Homework assessment

The homework consists of mandatory problems. Each problem will be graded and given the grade 3, 4, or 5. A minimum grade of 3 is required on each home problem in order to pass the course. Re-submissions of home problems will be allowed, but then only to reach the lowest grade.  Refer to the home problem descriptions for details regarding their individual grading.

Project assessment

The project work grade depends on the total accomplishment of the project, and a final report that well describes the solutions is required. For the grade of 4 or 5 an oral presentation is required, and will be scheduled on the students' request after the submission of the report. In addition, the project teams must demonstrate their progress during the course by the accomplishment of some sub-goals.

The students’ performance on the project will be evaluated and graded both on the group level and on the individual level in addition to the project assessment. If the contribution of an individual is found to be particularly strong or particularly weak, that will result in +1 or -1 in the final grade of that individual. Therefore, students of the same project group might end up with different project grades.

Individual team member assessment

Each team member will during the course individually assess fellow team members’ contributions in the project using a specific form, i.e. the Individual Team Member Assessment sheet. The form will be sent out after the project report was submitted. Each student shall then submit the form, via email to the course examiner, before receiving a grade on the project. Your answers will not be shared with anyone else! However, it is a delicate matter to do such judgements about other individuals, so please take on this responsibility with honesty and care.

Final course grade

The student’s final course grade will be determined according to the following principles: The mean value of the home problem grades (3, 4, or 5), plus the grade on the project work (3, 4, or 5), divided by two. The resulting value, rounded to the nearest integer value, is the final individual grade of the course.

In ambiguous cases, such as e.g. when the summation equals 4.5, the student’s overall performance in the course will also be taken into account. For example, it is more likely that the final grade will be a 5, in the above mentioned case, if the student has scored high in the individual tasks and the group grade was low, than in case of the opposite. In that latter case a final grade of 4 is more likely to occur.

Important: In the end of the course, an individual assessment meeting will be held with each student, where the examiner of the course will ask detailed questions about the submitted home problems and project work. If the student fails to give sufficient answers to these questions the grade might be lowered or blocked for further assessment. The questions will only assess the already approved work, and solely work as a final check for the grading. Therefore, the student should review all submitted content before the meeting, but is not expected to give further information than what was given in the submissions.

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).

The reports (and other submitted materials such as e.g. programming code) should be original work in order to be passed. Therefore, all reports and texts that you submit for grading and examination must be submitted via Urkund, which is a tool for detection of plagiarism. Please see the assignment descriptions for details about how to submit your reports via Urkund. Note that all suspected cases of plagiarism (not only those detected by Urkund) will be reported to the university disciplinary committee (disciplinnämnden)!

Course summary:

Date Details Due