Robotics Engineering - Engineering Science

Robots perform important tasks for us that are dangerous, difficult or time-consuming.

Robotics engineers create autonomous field robotics, healthcare robotics, and advanced manufacturing robotics for use in dynamic, unpredictable environments.

They work on technology as diverse as self-driving cars, rovers for space exploration, autonomous drones, and snake-like robots for finding earthquake survivors in rubble. They develop AI-powered nanobots for cancer therapy, social robots for long-term care, assistive devices, and biosensors that are revolutionizing healthcare. They design smart materials, large and tiny robot factories, and continuum robots for confined spaces in advanced manufacturing.

EngSci's Robotics Engineering major was launched in 2015 to meet the need for engineers in this rapidly growing field. Students benefit from the exceptional education and research strengths of the University of Toronto Robotics Institute, the largest and most diversified robotics institute in Canada.

Courses are taught by world-renowned faculty members from the University of Toronto Robotics Institute, the University of Toronto Aerospace Institute (UTIAS), and the Departments of Electrical & Computer Engineering, Mechanical Engineering, and Computer Science.

Students learn about the design of the key components of robotic systems including circuitry, algorithms and control systems. The curriculum focuses on perception, reasoning and acting as the three key functions of intelligent robots, with special focus on system integration through design and research opportunities.

Topics include mobile robotics, computer vision and perception, artificial intelligence and machine learning, robot modeling and system control, dynamics and control systems, and analog and digital electronics. Students also explore the relationship between robots and society, and are taught to design with ethical, social, economic and safety implications in mind.

Graduates are well-prepared for graduate studies or direct entry into the workplace with excellent knowledge in related disciplines, including machine learning, computer vision, control theory, dynamics, and mechatronics. They are able to translate a specific users' desired actions into design requirements for a suitable robotic system, and use a "systems approach" to design robotic systems in parts and as a whole.

FAQs

What are the key differences between and EngSci's Robotics Engineering and Machine Intelligence majors?

The Robotics Engineering major emphasizes a whole-system perspective of robotics, requiring knowledge of sensors, control, electro-mechanical systems and computer programming. Robotics engineers have a unique role in system integration and must understand how machine intelligence is used by robotic systems.

While machine intelligence is an important part of the multidisciplinary field of robotics, the Robotics Engineering major also provides training in the core robotics-related subjects of computer vision, control theory, dynamics, and mechatronics.

In contrast, the Machine Intelligence major teaches students the development and application of machine intelligence in a wide variety of industries and contexts.

Is this major the only way to study robotics engineering at U of T?

U of T Engineering offers several avenues for study in this field.

All Engineering undergraduates except those in the EngSci Robotics Engineering major can pursue the Robotics and Mechatronics minor.

The Mechanical Engineering Program also offers streams in mechatronics and manufacturing. Its curriculum focuses more on mechatronics, while there is a greater emphasis in the EngSci major on "autonomy" (i.e., providing robotics with artificial intelligence).

How many students from this major do a PEY Co-op after third year?

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Sample Courses

ROB301H1F Introduction to Robotics

The course provides a very broad and interdisciplinary introduction to the key aspects of robotics. The course structure is modular and reflects the perception-control-action paradigm of robotics. Applications covered include robotics in space, autonomous terrestrial exploration, biomedical applications such as surgery and assistive robots, and personal robotics. The course ends with a hardware project on robot integration.

AER521H1S Mobile Robotics and Perception

Students learn the fundamentals of mobile robotics and sensor-based perception for applications such as space exploration, search and rescue, mining, self-driving cars, unmanned aerial vehicles, autonomous underwater vehicles, etc. Topics include sensors and their principles, state estimation, computer vision, control architectures, localization, mapping, planning, path tracking, and software frameworks. Laboratories will be conducted using both simulations and hardware kits.

CSC384 Introduction to Artificial Intelligence

This course teaches the theories and algorithms that capture (or approximate) core elements of computational intelligence. Topics include: search; logical representations and reasoning, classical automated planning, representing and reasoning with uncertainty, learning, decision making (planning) under uncertainty. Assignments provide practical experience, both theory and programming, of the core topics.

ECE470H1S Robot Modeling and Control

Robot manipulators are used in many settings such as manufacturing, warehouses, and home care. This course provides a solid foundation on modelling and controlling these class of important robot. Topics include classification of robot manipulators, kinematic modeling, forward and inverse kinematics, velocity kinematics, path planning, point-to-point trajectory planning, dynamic modeling, Euler-Langrange equations, inverse dynamics, joint control, computed torque control, passivity-based control, feedback linearization.

MIE443H1S: Mechatronic Systems: Design and Integration

In this design course students work in teams to build an automated robot in a class setting that mimics the industrial design world. Lectures, tutorials and regular check-ins guide students through a step-by-step approach to the entire design process, from specification and conceptual design, through modeling and synthesis, to prototyping, integration and testing. Students learn project engineering methods and integration of complex automation. Although the emphasis is on mechatronics, the learned skills and knowledge are useful in all areas of system integration.

Where this major can take you

EngSci graduates are leaders in robotics-related industry and research. Meet some of our alumni.

Employers for recent graduates from this major include Accenture, AMD, DiDi Labs, Google, Intel, Qualcomm, and more.

Recent graduates have attended graduate school at Carnegie Mellon University, ETH Zurich, MIT, UC Berkeley, University of Michigan, U of T, and more.

Photo of Professor Jonathan Kelly wearing a grey suit jacket and pale blue shirt.

Chair of the Robotics Engineering major

Professor Jonathan Kelly (UTIAS)

Professor Kelly is the Director of U of T’s Space & Terrestrial Autonomous Robotics Systems (STARS) Lab. He works on developing robust autonomous systems capable of operating independently over long durations in challenging environments, e.g., in space and on remote planetary surfaces.

jkelly@utias.utoronto.ca