The Quanser Virtual QCar is a fully instrumented, dynamically accurate digital twin of the Quanser QCar system. It behaves the same way as the physical hardware and can be measured and controlled using the Python, ROS, and MATLAB Simulink development environments.
With a reconfigurable and visually rich environment that mirrors the physical Self-Driving Car Studio, it can enrich your lectures, labs, research, and outreach activities. Beyond the classroom and research lab, the platform offers the capacity to give students skills-based leaning experiences in a blended and/or hybrid configuration for distance and online courses.
To realize a fully-functional twin of the physical QCar, the virtual system is a complete mechatronic system with industrially relevant sensors such as LiDAR, and encoder, IMU, and RGB-D cameras.
The Quanser Self-Driving Car Studio is the ideal platform to investigate various research topics for teaching and academic research in an accessible and relevant way. Use it to jump-start your research or give students authentic hands-on experiences learning about the essentials of self-driving.
QCar, the feature vehicle of the Self-Driving Car Research Studio, is an open-architecture, scaled model vehicle designed for academic research. Working individually or in a fleet, QCar is the ideal vehicle for validating dataset generation, mapping, navigation, machine learning, artificial intelligence, and other advanced self-driving concepts.
QLabs Virtual Quanser AERO is a fully instrumented, dynamically accurate virtual twin of a Quanser AERO system. The platform is compatible with the physical Quanser AERO engineering curriculum.
