EECS 467: Autonomous Robotics Design Experience / Winter 2026

Course Description

Software methods and implementation for robot perception, world mapping, and control, using physical robots. Topics include: sensors, sensor processing, control, motion planning, localization and mapping, and forward and inverse kinematics. Multiple team projects, culminating in a major design experience (MDE) project.

Lecture / Lab

Day Time
Tuesday 12:00 PM – 1:30 PM
Thursday 12:00 PM – 1:30 PM
Friday 3:30 PM – 5:30 PM

Course Meetings

For EECS 467 Winter 2026, the course uses a “flipped classroom” model. Some lecture content is posted as pre-recorded lectures available online through PrairieLearn, together with lecture review exercises. We will work hands-on with robots during the in-person lecture and lab time. You are expected to complete assigned PrairieLearn HWs before class and attend lectures and labs in person.

Resource Link
Piazza (Q&A, announcements) piazza.com/umich/winter2026/eecs467wn26
Google Drive (notes, slides) EECS467 WN26 Shared
GitLab (projects & tutorials) gitlab.eecs.umich.edu/eecs467-wn26
Canvas (submissions & grades) canvas.it.umich.edu
PrairieLearn (HW & quizzes) us.prairielearn.com
Office Hours Calendar Schedule page
Lecture Videos YouTube Playlist
MBot Documentation mbot.robotics.umich.edu

ROB330 students: Use this separate Google Drive folder.

Grading

Component Weight
Part I – Course Introduction (Checkpoint 0: MBot Intro Assignment) 3%
Part II – Mobile Robotics / Botlab (Checkpoints 1–3 + Mini Project) 35%
Midterm Competition 5%
Part III – Design Project (Proposal + Update + Video + Final) 40%
PrairieLearn Lecture Review Exercises 5%
Quiz 10%
Participation 2%
Total 100%

Programming

Warning: Software development in C/C++ and Python is a major part of this course. Prior programming experience in C or Python (or a comparable language) is required. You may also find the ROS2 documentation helpful.

Collaboration Policy

Individual assignments must be submitted independently. For group assignments, each team must submit wholly original work. Teams are encouraged to discuss ideas but must produce independent write-ups and code. All team members are expected to understand every aspect of the team’s work. See the full syllabus on Google Drive for the full collaboration policy statement requirements.

Generative AI Policy

GenAI use is permitted with disclosure for most work. For programming assignments (Projects 0–4), PrairieLearn, and quizzes, GenAI may not be used to fill in code templates. For the final design project, GenAI may assist with ideation and editing as long as use is disclosed. See the full policy on the course syllabus.

Lab Equipment Policy

Lab equipment must not be removed from the lab without explicit authorization. Students must sign and return the MBot agreement. Report any hardware damage immediately to course staff.

Course Policies

  • Academic Integrity: All students are bound by the College of Engineering Honor Code.
  • Disability Accommodations: Contact SSD (734-763-3000) for accommodations.
  • Diversity: All members are expected to contribute to a respectful, inclusive environment.
  • Student Well-Being: Resources available at wellbeing.studentlife.umich.edu.

Previous Offerings and Project Showcase


Instructors

Teaching Assistants

Ashrith (Ash) Edukulla

Vaibhav Gurunathan

Ruey Day

Rishad Hasan

Jason (Jay) Brown