This is the official page of the Intelligent Mobility and Robotics Lab (IMRL) at the University of New Brunswick, Fredericton, Canada.

Lab Director’s Bio

Dr. Yukun Lu joined the Department of Mechanical Engineering at the University of New Brunswick as an Assistant Professor in July 2025. She earned her Ph.D. in Mechanical and Mechatronics Engineering from the University of Waterloo in 2023, where she continued as a Postdoctoral Researcher at the Mechatronic Vehicle Systems Lab. She holds a B.Eng. in Vehicle Engineering with a minor in Business Administration, completed in 2018. Her background and future research interests include ground vehicle corner modules, intelligent robotic mobility, data-driven learning-based control strategies, vehicle dynamics and control, etc.

Open Positions

Please send your CV and research interest to yukun.lu@unb.ca

1. MScE and PhD: We welcome applications from students with backgrounds in Mechanical & Mechatronics, Electrical Engineering, or Computer Science who are interested in pursuing graduate studies.
2. Postdoctoral Fellow and Visiting Scholar: Candidates with expertise in intelligent mobility, truck platooning, autonomous driving, and tracked vehicles are welcome to apply.
3. Research Assistant/Associate: Both full-time and part-time positions are available, with options for hybrid or fully remote work. Proficient in Python and ROS 2 for robotic platform development and integration.

Female candidates are strongly encouraged to apply!

Research Topics

Autonomous Log Loading and Transportation in Forestry

Log loading in forestry involves the use of specialized equipment, such as log loaders and cranes, to lift, move, and stack logs onto trucks or trailers for transport. To improve efficiency and safety in forestry operations, we aim to develop a modular autonomous platooning system equipped with assist log-loading technology.

Robotic Mobility with Tracked and Wheeled Corner Modules for Forestry and Agriculture

This robotic platform features a modular chassis capable of transitioning between tracked and wheeled mobility. The tracked system ensures superior traction on soft, uneven, or loose surfaces, making it ideal for navigating through mud, snow, or forest floors. The wheeled corner module system enhances maneuverability and speed on firmer ground, optimizing performance for mixed-terrain environments. We aim to develop a fleet of autonomous robotic mobility for sustainable land management in forestry and agriculture.

Autonomy for Ships and Submarines (Co-PI)

This project focuses on advancing autonomous marine systems in underwater environments. Research areas include: perception and localization for maritime autonomy, sensor fusion for enhanced situational awareness, wave simulation and pattern recognition, learning-based control for 3D printers and robots on marine platforms.

Collaborations

We actively collaborate with leading institutions worldwide, including: University of Waterloo, University of Alberta, University of Ottawa, University of Michigan, University of Hong Kong, etc.