Syllabus — Fall 2021

Syllabus draft — will be finalized soon.

1 Course Staff

InstructorProf. Mohamed-Ali Belabbas
Prof. Katie Driggs-Campbell
belabbas@illinois.edu
krdc@illinois.edu
Engineering Teaching Lab SpecialistDan Blockd-block@illinois.edu
Teaching AssistantsNeeloy Chakrabory
Peixin Chang
Dhruv Mathur
Yuhang Ren
Chuyuan Tao
neeloyc2@illinois.edu
pchang17@illinois.edu
dmathur2@illinois.edu
yuhangr2@illinois.edu
chuyuan2@illinois.edu

2 Time and Place

2.1 Lecture

Tuesdays and Thursdays from 12:30pm-1:50pm, in ECEB 1015 and streamed simultaneously. Lecture videos will be posted on Echo360.
Zoom information can be found on the course Discord. Please check your email or reach out to the course staff for an invitation link.

2.2 Laboratory

Labs will be held in ECEB 3071. Labs will start the second week of class.

For up to date information on labs as well as the section dates and times, check out the lab website: http://coecsl.ece.illinois.edu/ece470/

2.3 Office Hours and Homework Party

Office hours are available on the Office Hours page.

Homework Party (group office hours and study sessions) will be held Fridays from 4pm-6pm in ECEB 2013. (Starting 9.03)

See description below in course content.

3 Course Description

The robotics industry is in a period of rapid growth. This course will cover the fundamentals of modeling, perception, planning, and control, that you need to enter this industry and take advantage of the opportunities presented by it. This course will introduce you to standard modeling and control techniques as well as modern ways of thinking about robotics that are based on methods of optimization and learning. Consistent with these ways of thinking, this course will place a strong emphasis on computation.

4 Prerequisites

You must be willing to code in MATLAB, python, and in C++. You must be willing to use analytical tools drawn from linear algebra, differential calculus, and basic probability theory.

5 Reference Texts

[required] Modern Robotics, Lynch and Park, Cambridge University Press, 2017
– authors’ site (free version, video lectures): http://lynchandpark.org
– publisher’s site: Cambridge University Press https://goo.gl/U5uZdu
[suggested] Probabilistic Robotics, Thrun, Burgard, and Fox, MIT Press, 2005
– authors’ site: http://www.probabilistic-robotics.org/

Supplementary material will be made available with the posted lecture notes on the Schedule and Extras page.

6 Grading

  • exams = 35% (17.5% each)
  • HW = 20%
  • Project = 20%
  • Lab = 20%
  • Participation = 5%

The final grades will be curved, but you can expect the following scale: 90-100 (A), 80-89 (B), 70-79 (C), 60-69 (D), >60 (F).

More information about each of these items is provided in the course content section below.

7 Course Content

7.1 Participation

Participation is an important part of this course and will be measured in a number of different ways. Like most courses, you will get credit for positive contributions to the course, for example: being active on discord, helping others in office hours, providing interesting insights or discussion points, contributing in class, etc. You will also get participation for:

  • Attendance: During some lectures, attendance will be taken. Attendance will be taken during every guest lecture.
  • Homework Parties: Every Friday from 4:00-6:00pm in ECEB 2013, there will be a homework party: a group office hours where you may work on homework or the project and get help from other students as well as the TAs (at least two TAs will be present at all times). Assisting other students will be noted by the course staff and contribute to your participation grade.
  • Shout outs: To recognize a fellow student for outstanding positive contributions (i.e., participation), fill out this shout out form {link TBD}, which will be open until the end the semester. Note that you will be required to be logged in through your Illinois account.

7.2 Homework

There will be mixture of written and PraireLearn* assignments. Written assignments will be submitted via Gradescope. Deadlines are posted in the important dates tab.

* PrairieLearn (https://prairielearn.engr.illinois.edu) is system that will give you instant feedback on each question (right or wrong) and allow multiple attempts with no penalty.

Homework will be due on Fridays at 8pm CT.  No homework assignments will be dropped.
For one week after the deadline, you may submit a late assignment for up to 50% credit.

7.3 Midterms

There will be two midterm exams throughout the semester. Details on proctoring will be posted soon.

7.3.1 DRES Accommodations

If you have accommodations identified by the Division of Rehabilitation-Education Services (DRES) for exams, please send your Letter of Accommodation (LOA) to the course instructors as soon as possible to make the adjustments.

7.4 Group Project

Throughout the semester, you’ll be working in small teams (up to 3 members) on a final project.  In this project, you are expected to simulate a robot (of your choice) to complete some task (of your choice). You’ll be asked to integrate each topic of the course into your robot pipeline (concrete details to be provided on the website) and put together a compelling pitch to “sell” your intelligent robot. Every few weeks there will be a checkpoint (referred to as a project update), to make sure you’re making progressing and implementing course content.  At the end of the semester, you’ll give a short presentation to the class and submit a final report.  This report will take the place of a final exam.

Example reports and videos can be found on the project page.

7.5 Laboratory

You will attend weekly laboratory sessions. Attendance is required, unless a written explanation is obtained from the emergency dean. You will work in groups to do in-lab activities, will show in-lab demos to your TA, and will submit reports. Details will be posted here:  http://coecsl.ece.illinois.edu/ece470/.

Lab reports will be submitted through Gradescope.  Please contact an instructor if you have not been added to the class roster.

7.6 Extra Credit

No homeworks or exams will be dropped from the course.  However, there is an opportunity for extra credit.

You can do an extra credit project that will count for a bonus added to your total grade (roughly weighted as one homework). You may submit an informational/tutorial video on your favorite topic in the class.  In a visual way, this video should motivate why this topic is important, explain the fundamentals, walk through an example problem, and provide resources for further study. For inspiration, check out 3Blue1Brown or the Kahn Academy on YouTube.

Guidelines: The videos should be ~5 in length. You will be scored on 0-5 on the following:
– Is the video a good length?
– How challenging is the topic?
– Did you provide an interesting motivating example?
– How well did you explain the topic?
– Did you provide an informative worked example?
– How effective are the visualizations used?
– Does the video demonstrate creativity in teaching?
Submission details will be provided soon.

8 Website, Access, and Correspondence

All materials and updates will be posted here on our course website.

We have set up a discord for course discussion. All correspondence with the TAs will be through discord. Note that the instructors will not be available through discord.

Note that discord is not a perfect replacement for Piazza. If you do not get a response from the TAs or your peers within 24 hours, please repost your question or ping the TAs directly. Also, note that you can earn participation points by actively answering questions on discord and helping out your fellow students.

All announcements will be sent out via discord and email.