Welcome to the CS AI Robotics (CAR) Lab
Welcome to the central hub of advanced robotics and artificial intelligence research at Lawrence Technological University. The CAR Lab provides undergraduate and graduate students with hands-on environments to develop production-ready software systems for autonomous mobility. We focuses on expanding the frontiers of autonomous platforms, computer vision applications, sensor fusion, application of deep learning for autonomous robotics, and intelligent vehicle engineering.
Explore our latest projects, join our competitive teams, or read through our recent publications using the navigation menu above.
The MCS lab was founded by Dr. CJ Chung Professor of Computer Science in 1999. MCS Dept Chairs James Nanny (1998) and David Bindshadler (1999) gave full support for the start of the lab in CW21. The lab was the birthplace of Robofest (in 1999) and the Home of MCS IGVC teams (2003-)
History of Lab Locations
1999 - 2011: Room CW21
2007 - 2017: Room M218
2011 - 2021: Room M137
2021 - present: Room M215A
Lab Members
Faculty Directors
- Dr. CJ Chung - Professor, Math and Computer Science Dept. (Founding Director since 1999)
- Dr. Vijay John - Associate Professor, Math and Computer Science Dept.
Research Assistants
- Devson Butani (Rearch Manager)
Former Lab Assistants
- Devson Butani (2014-2025)
- John Ruszala (2009-2016)
- Maurice Tedder
- Jeremy Gray (2008-2009
- Rita Chen
- Emily Trudell
- Sara Moss
- Jason Lo
- Jason Chang (2001)
- ...
Intelligent Ground Vehicle Competition (IGVC)
Our flagship autonomous platform is designed from scratch to navigate complex outdoor obstacle courses without human intervention, leveraging advanced lane detection algorithms and GPS waypoints.
RoboCup
Autonomous Self-Driving Car
Utilizing full-scale drive-by-wire converted platforms to implement end-to-end path planning, path tracking, and localized mapping frameworks inside dynamic urban mock-up environments.
Computer Vision & Machine Learning
Developing lightweight real-time object detection pipelines capable of running edge-computing workloads natively on vehicular microchips.