This course is coming January 2018 … Stay tuned for further details.


The objective of this course is to introduce students to the fundamentals of autonomous ground vehicles engineering.  The course focuses on those tasks usually carried out by autonomy engineers, including sensor selection, vehicle modelling and design, applied control (e.g., trajectory and path following) and navigation/state estimation techniques for robotic wheeled vehicles that operate in real environments (e.g., mining, construction, warehouses, roadways, etc.).   This course does not focus (extensively) on planning algorithms, machine learning, computer vision, or other specialty fields, although these are of course also highly relevant to the world of autonomous vehicles.

The audience is graduate students from all relevant engineering and applied science disciplines who have an interest in mobile robotics, applied control and estimation, and robotic vehicle applications.


It is strongly recommended that students have taken at least one undergraduate-level course in control systems engineering, such as MECH 350, ELEC 443, or at least a similar/related course.


This is a 12-week course that involves both lectures and tutorials (i.e., hands-on workshops where simulation is used to apply techniques introduced in the course) every week.  Students are also expected to complete and present an independent project.  The grading scheme is as follows: 20 % (two assignments), 40 % independent project, 40 % final exam.