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Self-Driving Car Studio

Virtual platform for distance and blended undergraduate aerospace and controls courses

Autonomous Systems & Applied AI Autonomous Vehicle Control Mobile Robotics

The Quanser Self-Driving Car Studio is the ideal platform to investigate a wide variety of 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. The studio brings you the tools and components you need to test and validate dataset generation, mapping, navigation, machine learning, and other advanced self-driving concepts at home or on campus. 

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Product Details

At the center of the Self-Driving Car Research Studio, the QCar, is an open-architecture scaled model vehicle, powered with NVIDIA® Jetson™ TX2 supercomputer, and equipped with a wide range of sensors, cameras, encoders, and user-expandable IO.

Relying on a set of software tools including Simulink®, Python™, TensorFlow, and ROS, the studio enables researchers to build high-level applications and reconfigure low-level processes that are supported by pre-built modules and libraries. Using these building blocks, you can explore topics such as machine learning and artificial intelligence training, augmented/mixed reality, smart transportation, multi-vehicle scenarios and traffic management, cooperative autonomy, navigation, mapping and control, and more.

Dimensions 39 x 21 x 21 cm
Weight (with batteries) 2.7 kg
Power 3S 11.1 V LiPo (3300 mAh) with XT60 connector
Operation time (approximate)  ~2 hours 11 m (stationary, with sensors feedback)
30 m (driving, with sensor feedback)
Onboard computer NVIDIA® Jetson™ TX2
CPU: 1.2 GHz quad-core ARM Cortex-A57 64-bit + 1.2 GHz Dual-Core NVIDIA Denver2 64-bit
GPU: 256-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, magnetometer)
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 feautres Headlights, brake lights, turn signals, and reverse lights (with intensity control)
Dual microphones
Speaker
LCD diagnostic monitoring, battery voltage, and custom text support

 

Dimensions 39 x 21 x 21 cm
Weight (with batteries) 2.7 kg
Power 3S 11.1 V LiPo (3300 mAh) with XT60 connector
Operation time (approximate)  ~2 hours 11 m (stationary, with sensors feedback)
30 m (driving, with sensor feedback)
Onboard computer NVIDIA® Jetson™ TX2
CPU: 1.2 GHz quad-core ARM Cortex-A57 64-bit + 1.2 GHz Dual-Core NVIDIA Denver2 64-bit
GPU: 256-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, magnetometer)
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 feautres 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 Autonomous Software License
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

 

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