Michael is a second-year MASc candidate in Mechanical and Materials Engineering under the supervision of Joshua Marshall. For Michael’s thesis, he will continue with his research on a learning-based predictive path following control system. The principle of this control strategy is to combine the known benefits of predictive control but also use learned information from the environment to better model and predict the vehicle’s behaviour.
To implement his research, Michael is using a Clearpath Husky and the Offroad Robotics Kubota RTV900 autonomous vehicles for field testing. To test and validate the control strategies, Michael is doing his testing at an indoor ice rink to subject the robots to the most challenging terrain.
Footage of Michael and the Clearpath Husky testing at Centre 70 Arena in Kingston, ON. 
Early testing session at Centre 70 Arena in Kingston, ON to understand the challenges faced when driving on ice. 
Michael and colleague, Jeremy Roy, doing field testing on Queen’s campus with the RTV900
Contact
Ingenuity Labs Research Institute, Queen’s University
Mitchell Hall, Room 245
69 Union St West
Kingston, ON K7L 3N6
Canada
Email: m.fader@queensu.ca
External Links
TA Courses
- MECH 350 – Automatics Control – Winter 2019, Winter 2020
- MECH 452 – Mechatronics Engineering – Fall 2018, Fall 2019
Undergraduate Research
Fader. M, Long Range Object Tracking Using Infrared and Ultrasound Optical Sensors, BASc Thesis, Department of Mechanical and Materials Engineering, Queen’s University, Kingston ON, April 2018 (Supervisor: Brian Surgenor)