Assignments

This is general information for the assignments. For specific information on each assignment, including deadlines, please see the assignment pages (linked below).

Please note that some details regarding the course may change up until the first lecture, and that additional information may be added to this Canvas site.

 

Deadlines:

For grading:

There is a common deadline (October 11, 17:00) for the assignments. In order to be eligible for a C grade or higher on an assignment, it has to be completed to at least a passing grade (E) by this deadline. All deadlines are hard, missing it by a minute means you have missed it - you are responsible for having enough time margins. For assignments 2-4, you must be registered in Kattis by the time of submission for your submission to count, e.g. if you upload it before the deadline and register after the deadline, you have submitted after the deadline.

For bonus points:

There is an individual deadline for each assignment. Completing the assignment by this deadline (typically the week after each assignment has been presented, check individual descriptions for details) will give you bonus points towards the exam score.

 

Instructions:

There is a page with instructions for each assignment. These can be found in the corresponding modules, or via the links in the text below. Each assignment will also be presented via Zoom, where a TA will give detailed instructions and answer questions if anything is unclear. Links to instruction sessions can be found here, and in each module.

Help

If you need help with the assignments, you can either ask questions on the discussion boards, or ask the TAs in the help sessions - scheduled as 'lab' in the schedule. Use the online queue to sign up for help.

 

Grading:

Assignment 1 - (ROS Basics) is graded as P/F. This assignment should be presented to the TA's during regular lab hours. Satisfactory presentation by the deadline gives 3 bonus points towards the exam.

Assignments 2-4 - (Kinematics, Planning, and Mapping) are graded as E or C. These assignments are submitted to the Kattis autograding system. There are different requirements for the grades E or C, see each assignment for details. Assignments that fullfill the requirements for E by the respective deadlines are awarded with 3 bonus points. Fulfilling the requirements for a C grade by the respective deadlines is awarded with an additional 2 bonus points, for a total of 5. The maximum possible bonus for completing all three assignments on time is thus (3*(3+2)) = 15 bonus points. Details regarding requirements for different grades, and deadlines can be found on the individual pages for each assignment. These assignments are completed individually.

 

Project Assignment - (Mobile pick-and-place), is graded as E, C, or A. This assignment should be presented to the TA's at a scheduled lab session, the latest at Friday, Oct 11. There are different requirements to fulfill for the different grades, see assignment description for details. Completing this assignment to an E level by the deadline is rewarded with 3 bonus points, a C level by the deadline with 5 bonus points, and an A level with 7 bonus points.

Note: the maximum possible amount of bonus points is 25, awarded if all assignments are completed and handed in on time, to the maximum grades.

 

Grades for the assignments will be reported 3 times during the fall semester: at their respective deadline, and at the time of the exam in P1, and at the time of the make-up exam in P2. This means that if you submit an assignment shortly after a reporting deadline, it may take considerable time until your result is reported.

 

Assignments that had a passing grade by the deadline (Oct 11) can be submitted for a higher grade up until the time of the make-up exam in P2, i.e. 17:00 December 16. Assignments that are submitted after this, or without a completed Kattis registration, will not be considered for grading.

 

Kattis (Note: Mandatory registration)

Course page in Kattis: https://kth.kattis.com/courses/DD2410/irob24
Log in to Kattis with your KTH account!
You must complete the following registrations steps. Logging in without registering means that your submitted problems are not forwarded to the teachers, and will not be graded. Registration is a hard requisite for being graded, and registration after the deadline will count as submission after the deadline.!

  1. Registered for the course in Kattis (click on I am a student taking this course and I want to register for it in Kattis Links to an external site.).

    Screenshot from 2022-09-06 08-59-20.png


    When you have done the first step of registration, you should see this on your screen:
    Screenshot from 2022-09-06 08-59-36.png



  2. If prompted to enter a team name, make sure it is identical to your student name. Your 'Team name' is what we will see in the results list.



    About Kattis

    Kattis is the autograding system used by the EECS school. It is used for assignments 2, 3, and 4 in this course. See each assignment for instructions on what and how to submit. All submissions to Kattis are made with your personal KTH log-in. Kattis is equipped with a plagiarism checker, and if another student's solution is submitted with your account, this will count as attempted plagiarism. Only submit your own code into Kattis, do not use your account to try out a friend's solution to an assignment. Your friend can easily submit their code with their own account.

    Kattis is not a debugging tool. Ensure that all your code works in your own development environment, with all the supplied practice test cases, before submitting to Kattis. A more in depth description of what the Kattis answers mean can be found here: https://open.kattis.com/help/judgements Links to an external site. .

    Most notable, Kattis does only provide the basic python libraries + numpy as the only external library. If you keep getting "Runtime Error", submit the empty skeleton with only the include statements to see if the library is available. The problems are all solvable with the standard libraries + numpy.