User libraries and content resources for using Quanser products, including research examples, teaching content, user manuals, guides and more.
Quanser Interactive Labs is a platform that allows users to interface with digital twins of physical lab experiments used for Controls and Robotics courses at thousands of universities around the world.
Designed a system that can efficiently sort recyclables and transfer them to corresponding bins using Python, a Raspberry Pi, and Quanser Labs.
End-to-end vision-based autonomous navigation on Quanser QCar. ENet lane segmentation, YOLOv8 traffic detection, and RealSense + RPLidar AND-logic sensor fusion. Distributed laptop–Jetson architecture, 18–22 FPS, <50 ms TCP/IP latency.
• Developed an autonomous driving system (QCar2) on NVIDIA Jetson integrating LiDAR, CSI cameras, and Intel RealSense depth sensor for real-time perception • Trained and deployed RT-DETR model for traffic sign detection achieving 92.6% mAP and 24 FPS, enabling future integration into decision-making pipelin
Controlling a high-power quanser robotic arm with a hand-made Galileo Shield
Sending a Qbot a set of conditions via a rasberry pi to sort different bottles in a recycling station
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