The objective of this course is to introduce graduate-level engineering students to the fundamentals of autonomous vehicle control, localization, and mapping. This course focuses on those tasks usually carried out by autonomy engineers, including sensor selection, applied control (e.g., trajectory and path following) and navigation techniques for autonomous vehicles that operate in real environments (e.g., construction, warehouses, roadways, mining, etc.). Although the focus in this course is on ground vehicles, the presented methods are also applicable more broadly. The audience is engineers from all relevant engineering and applied science disciplines who have an interest in mobile robotics, applied control and estimation, and robotic vehicle applications. 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.
The next offering of ELEC 845 will be in the fall term of 2023. Enquires about registration should be directed to Debie Fraser in the Department of Electrical and Computer Engineering at Queen’s University. The first lecture is on September 5, 2023 at 9:30AM in Mitchell Hall, Room 126.
- It is strongly recommended that students have taken at least one undergraduate course in control systems engineering (e.g., at Queen’s, MECH 350, ELEC 443, MTHE 332, or something similar from elsewhere).
- Students should be comfortable with (vector) calculus and linear algebra, as well as have a strong grasp of the fundamentals of probability and statistics.
- It is assumed that students are proficient in basic programming in Python, MATLAB, Julia, or some similar language for numerical computing.
Details about the Course
This is a 12-week course that involves both lectures and regular hands-on activities where computer simulation is used to apply and experiment with introduced techniques and algorithms. Students are also expected to complete and present a significant independent project. The grading scheme comprises 20 % (two assignments), 40 % independent project, 40 % final exam.
Click here to view the draft Fall 2023 ELEC 845 Syllabus.
Click here to view the draft Fall 2023 project description handout.
Example Python Code
Click here to view the example Python code used in this course.