GRADUATE RESEARCH PROGRAM

Collaborative Specialization in Robotics (MASc, MSc, PhD)

Questions?

For questions about the Collaborative Specialization in Robotics, course substitutions or to receive documentation that you completed the Collaborative Specialization, contact robotics.gradstudies@utoronto.ca.

If you have questions related to course enrolment, finding a supervisor or course eligibility, contact the graduate advisor in your home department or institute.

Robotics is a fast-changing, highly interdisciplinary field. From health-care to manufacturing and customer service, the design and operation of robots is reshaping society and reimagining industries across the globe.

Launched in 2022 by the University of Toronto Robotics Institute, the Collaborative Specialization in Robotics is the only program of its kind in Canada that provides research-stream graduate students with a robotics designation on their transcript.

The program offers a structured community of practice that combines engineering and computer science approaches to robotics and its applications, including healthcare, mobility, and logistics and manufacturing. It also complements students's research thesis and coursework with a seminar-style course featuring high-profile robotics researchers from across Canada and around the world.

Students who enrol and complete the program will demonstrate a foundational understanding of robotics systems and core concepts to future employers in academia or industry, such as algorithms, design and integration approaches, that cut across robotics applications.

Program Eligibility

The Collaborative Specialization in Robotics is open to research-stream graduate trainees already admitted to a participating research-stream master’s degree program or PhD program at the University of Toronto. Participating degree programs include:

Aerospace Science and Engineering (UTIAS) — MASc, PhD
Biomedical Engineering (BME) — MASc, PhD
Computer Science (CS, MCS) — MSc, PhD
Electrical and Computer Engineering (ECE) — MASc, PhD
Mechanical and Industrial Engineering (MIE) — MASc, PhD
Rehabilitation Science — MSc, PhD

You must be supervised by a faculty member of a participating degree program.

You must be pursuing a thesis where the robotics connection is clear and tangible.

You must meet all of the above criteria to enrol in the Collaborative Specialization in Robotics.

You are NOT eligible to participate in the Collaboration Specialization in Robotics or enrol in ROB1830Y if:

You are not currently enrolled at the University of Toronto in one of the participating degree programs listed above.
You have already completed the Collaborative Specialization in Robotics at the master’s level and are currently enrolled in a PhD program.
You are enrolled in an MEng program. MEng students interested in pursuing a robotics designation should enrol in the Graduate Emphasis in Robotics.

Program Requirements

To graduate with a Collaborative Specialization in Robotics, you must meet the following requirements:

Complete a research-based robotics-focused thesis.
Complete one half course (0.5 FCE) from the below course list.
Attend at least eight seminars in ROB1830Y, the Robotics Institute Seminar Series (0.0 FCE, Credit/No Credit) in addition to your home program requirements. ROB1830Y is a continuous course, which means you can remain registered in the course across multiple years until you meet the course requirements (i.e. you don’t need to attend eight seminars in one year).
Meet the degree requirements of the School of Graduate Studies, and your graduate program.

How to enrol and complete the Collaborative Specialization in Robotics

Declare your intent to pursue the Collaborative Specialization in Robotics by completing the declaration form. This form is processed three times each year. The deadlines to complete the form are: September 5, January 5 and April 25.
Once your form is processed, you will be registered for the seminar course ROB1830Y on Acorn by either September 10, January 10 or May 1, depending on when you complete the declaration form.
Keep a record of your Robotics Institute Seminar Series attendance by capturing the name of the speaker, seminar title and the date you participated or watched the seminar. Note: Your seminar attendance will be verified. You can remain registered in the course over multiple years until you meet the course requirements (i.e., you do not need to attend eight seminars in one academic year.)
Once you've met the requirements of the Collaborative Specialization by completing your thesis and seminar course requirements, fill out the Collaborative Specialization Completion Form by October 10 (for November convocation), February 10 (for March convocation), May 10 (for June convocation).
The Robotics Institute Education Committee will review your submission to assess completion. If your submission is approved, a letter indicating the successful completion of the Collaborative Specialization in Robotics will be provided to the School of Graduate Studies and your home department or institute.
Graduate with the Collaborative Specialization in Robotics on your transcript.

Important Forms

Courses

NOTE: Not all courses will be offered every year.

Group 1 Planning and Control

AER1516H: Motion Planning for Robotics
AER1517H: Control for Robotics
ECE557H: Linear Control Theory (Exclusion: ECE410H)
ECE1619H: Linear Geometric Control Theory
ECE1658H: Geometric Nonlinear Control of Robotic Systems
ECE1636H: Control of Discrete-Event Systems I
ECE1647H: Introduction to Nonlinear Control Systems
ECE1653H: Hybrid Systems and Control Applications
ECE1657H: Game Theory and Evolutionary Games
MIE1064H: Control Methods with Applications To Robotics
MIE1068H: Nonlinear Control
ECE1635: Special Topics in Control I
ECE1505: Convex Optimization

Group 2: Perception and Learning 

AER1513H: State Estimation for Aerospace Vehicles
AER1515H: Perception for Robotics (Exclusion: ROB1514)
CSC2503H: Foundations of Computer Vision
CSC2506H: Probabilistic Reasoning
CSC2515H: Introduction to Machine Learning
CSC2541H: Topics in Machine Learning
CSC2548H: Machine Learning in Computer Vision
ECE516H: Intelligent Image Processing
ECE1511H: Signal Processing
ECE1512H: Digital Image Processing and Applications
JEB1433H: Medical Imaging
ROB501H: Computer Vision for Robotics
STA2104: Statistical Methods for Machine Learning II
ECE1513: Intro to Machine Learning (cannot substitute with CSC2515)
CSC2606: Continuum Robotics
MIE1077: Artificial Intelligence for Robotics III (AIR III): Advanced AI-Based Robot Applications
ECE1508H: Special Topics in Communications: Applied Deep Learning
ECE1508H: Special Topics in Communications: Reinforcement Learning

Group 3: Modelling and Dynamics

AER506H: Spacecraft Dynamics and Control I
AER1503H: Spacecraft Dynamics and Control II
AER1512H: Multibody Dynamics
MIE1001H: Advanced Dynamics
MIE1005H: Theory of Vibration
JEB1444H: Neural Engineering
CSC2626: Imitation Learning for Robotics

Group 4: Systems Design and Integration 

AER525H: Robotics (Exclusion: ECE470H)
AER1216H: Fundamentals of UAVs
AER1217H: Development of Autonomous UAVs
CSC2621H: Topics in Robotics
ECE470H: Robot Modeling and Control (Exclusion: AER525H)
MIE1070H: Intelligent Robots for Society
MIE1071H: Advanced Robotics
MIE1075H: AI Applications in Robotics
MIE1809: Advanced Mechatronics
MIE505H: Micro/Nano Robotics
MIE506H: MEMS Design and Microfabrication
ROB 521H: Mobile Robotics and Perception
ROB 1514H: Introduction to Mobile Robotics
ROB 1830Y: Collaborative Specialization in Robotics Seminar Series
MIE1076: AI Applications in Robotics II
MIE1080: Introduction to Healthcare Robotics
MIE 1050: Design of Intelligent Sensor Networks

Questions?

If you have questions related to course enrolment, finding a supervisor or course eligibility, contact the graduate advisor in your home department or institute.