M.S. in Robotics Coursework
Take classes in several departments across the College of Science and Engineering as part of the M.S. in Robotics program. We pair real-world issues with an educational setting, and our industry collaboration allows students to connect to multiple outlets in Minnesota companies and beyond.
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Course Listing
This Minnesota Robotics Program is designed to be completed over the course of three semesters for a total of 31 credits. One course will be required from each key area (for a total of 9 to 10 credits), selected from a shortlist of foundational courses for each area. The remaining credits will be for the capstone (3 to 6 credits), thesis credits (10 credits), or the Robotics Colloquium (1 credit), with the remaining credits coming from a list of elective courses from participating departments.
You can view more information about each course in the University of Minnesota's M.S. in Robotics program catalog.
Note: Prerequisite will be implemented Fall 2024
| Course | Enforced Prereq |
| CSCI 5511 - Artificial Intelligence I | Graduate Student Standing |
| CSCI 5512 - Artificial Intelligence II | Stat 3021 and (CSci 3041 or 4041)) or Graduate Student Standing |
| CSCI 5521 - Introduction to Machine Learning | STAT 3021, (CSci 2033 or Math 2142 or Math 4242) |
| CSCI 5525 - Machine Learning | CSci 5521 |
| CSCI 5561 - Computer Vision | CSci 5521 |
Robotics Colloquium (1 credit) — Required
- The Robotics Colloquium will be an introductory class in which new students will be confronted with the basics of robotics and sensing while getting an idea of the industry, opportunities, and how the Minnesota Robotics Institute's Master's program can work for them.
Key Areas (9 to 10 credits total) — Choose one (1) from each area.
- Cognition
- Computer Science 5511 - Artificial Intelligence I (3 cr)
- Computer Science 5512 - Artificial Intelligence II (3 cr)
- Computer Science 5521 - Intro to Machine Learning (3 cr)
- Computer Science 5525 - Machine Learning: Analysis and Methods (3 cr)
- EE 5521 - Machine Learning & Data Science for ECE and ROB Students (3 cr)
- Perception
- Computer Science 5561 - Computer Vision (3 cr)
- Electrical Engineering 5271 - Robot Vision (3 cr)
- Electrical Engineering 5561 - Image Processing and Applications (3 cr)
- Robot Modeling and Control:
- Computer Science 5551 - Introduction to Intelligent Robotic Systems (3 cr)
- Computer Science 5552 - Sensing/Estimation in Robotics (3 cr)
- Mechanical Engineering 5286 - Robotics (4 cr, includes a lab)
- Electrical Engineering 5231/Aerospace Engineering and Mechanics - 5321 Linear Systems and Optimal Control/Modern Feedback Control (3 cr)
Final Projects — Choose one (1), either Plan A: Master's Thesis OR Plan B: Capstone project
- Plan A: Master's Theses (10 cr): Master’s theses (Plan A) will be supervised by a faculty advisor and follow the university rules. Students will have a committee of at least three faculty, write a thesis, and defend it orally to their committee. The Master’s thesis is especially useful for students considering later transferring to a Ph.D. degree or interested in a deeper research experience. View the Plan A student planning checklist for definitive grade and credit requirements and milestone and policy procedures for Plan A.
- Plan B: Capstone Project (3 - 6 cr): Capstone projects are supervised by faculty and may also be conducted in collaboration with industry partners. A capstone project will require at least one semester (3 cr for the Plan B course) but can be extended to two semesters. Students will document their capstone work in a final report and present their work in a video presentation to their final exam committee of 3 faculty members. View the Plan B student planning checklist for definitive grade and credit requirements and milestone and policy procedures for Plan B.
Elective Courses (fill in credit total to 31 credits) — Choose up to six (6) additional classes
Students may also use courses from the key areas below as electives, though a course can only count toward the program's core course requirement or the elective requirement, not both.
Please visit the Student Handbook to view the current list of approved elective courses. If there is a course you would like to take as an elective but is not approved, you can submit an approval request here.
Key Areas:
- Aerospace Engineering and Mechanics
- Biomedical Engineering
- Computer Science
- Design
- Electrical Engineering
- Finance
- Industrial and Systems Engineering
- Human Factors
- Mechanical Engineering
- Product Design
- Psychology
- Robotics
Industry and Academic Collaboration
- Courses are paused in the summertime to allow students to participate in highly coveted and competitive internships and programs in the industry.
- As mentioned under the benefits section, MnRI faculty is connected to key industries and top companies in the state of Minnesota and beyond. We are currently adding on-campus staff from Honeywell, and there are vast research options in the state of Minnesota, which has large local presences from 3M, Amazon, Honeywell, Toro, General Mills, Boston Scientific, Medtronic, Land O'Lakes, and much more.
- MnRI enjoys many benefits of connecting to about three dozen faculty from across the University of Minnesota. However, the connections do not stop in the Twin Cities. We entertain almost weekly speakers from across the world to talk about their research and issues within the robotics industry and collaborate with many educational and governmental institutions.