QCar, the feature vehicle of the Self-Driving Car Research Studio, is an open-architecture, scaled vehicle designed for academic research. It is equipped with a wide range of sensors including LIDAR, 360-degree vision, depth sensor, IMU, encoders, as well as user-expandable IO. The vehicle is powered with an NVIDIA® Jetson™ TX2 supercomputer that gives you exceptional speed and power efficiency.
Working individually or in a fleet, QCar is the ideal vehicle for validating your research concepts such as dataset generation, mapping, navigation, machine learning, artificial intelligence, and many more.
Training contents:
- Research and build control algorithms to control Qcar.
- Research on Image Processing.
- Research Deep Learning and AI.
- Research and develop concepts such as dataset generation, mapping, navigation, machine learning, artificial intelligence, and many more
- Build algorithm models using Matlab/Simulink, Python, C++ and ROS to develop practical applications.
Qcar
Features
- High Performance: NVIDIA® Jetson™ TX2 supercomputer
- Open Software Architecture: Design and deploy applications using Simulink®, Python™, C/C++, TensorFlow & RO
- Dependable: Robust mechanical design
- Extensive & Expandable: Wide range of sensors with user-expandable IO for custom applications
Device Specifications
- Dimensions: 39 x 19 x 20 cm
- Weight (with batteries): 2.7 kg
- Power: 3S 11.1 V LiPo (3300 mAh) with XT60 connector
- Operation time (approximate):
+ 2 hr 11 m (stationary, with sensor feedback)
+ 35 m (driving, with sensor feedback)
- Onboard computer
+ NVIDIA® Jetson™ TX2
+ GPU: 2 GHz quad-core ARM Cortex-A57 64-bit + 2 GHz Dual-Core NVIDIA Denver2 64-bit
+ GPU: 256 CUDA Core NVIDIA Pascal™ GPU architecture, 1.3 TFLOPS (FP16)
+ Memory: 8GB 128-bit LPDDR4 @ 1866 MHz, 59.7 GB/s
- Lidar: LIDAR with 2k-8k resolution, 10-15Hz scan rate, 12m range
- Cameras
+ Intel D435 RGBD Camera
+ 360° 2D CSI Cameras using 4x 160° FOV wide angle lenses, 21fps to 120fps
- Encoders: 720 count motor encoder pre-gearing with hardware digital tachometer
- IMU: 9 axis IMU sensor (gyro, accelerometer, magnetomter)
- Safety features: Hardware “safe” shutdown button Auto-power off to protect batteries
- Expandable IO
+ 2x SPI
+ 4x I2C
+ 40x GPIO (digital)
+ 4x USB 3.0 ports
+ 1x USB 2.0 OTG port
+ 3x Serial
+ 4x Additional encoders with hardware digital tachometer
+ 4x Unipolar analog input, 12 bit, 3.3V
+ 2x CAN Bus
+ 8x PWM (shared with GPIO)"
- Connectivity
+ WiFi 802.11a/b/g/n/ac 867Mbps with dual antennas
+ 2x HDMI ports for dual monitor support 1x 10/100/1000 BASE-T Ethernet"
- Additional QCar features:
+ Headlights, brake lights, turn signals, and reverse
lights (with intensity control)
+ Dual microphones
+ Speaker
+ LCD diagnostic monitoring, battery voltage, and custom text support
- Supported Software and APIs:
+ QUARC for Simulink®
+ Quanser APIs
+ TensorFlow
+ TensorRT
+ Python™ 2.7 & 3
+ ROS 1 & 2
+ CUDA®
+ cuDNN
+ OpenCV
+ Deep Stream SDK
+ VisionWorks®
+ VPI™
+ GStreamer
+ Jetson Multimedia APIs
+ Docker containers with GPU support
+ Simulink® with Simulink Coder
+ Simulation and virtual training environments (Gazebo, QuanserSim)
+ Multi-language development supported with Quanser Stream APIs for inter-process communication
Unreal Engine
Ground Control Station
Includes:
- High-performance computer
- Three monitors
- High-performance router
- Wireless gamepad
- QUARC Autonomous license
Accessories for road patterns
- Studio Space: 65 m2
- Set of reconfigurable floor panels with road patterns
- Set of traffic signs
