QCar

2022年10月04日配信

quanser_QCAR

Self-Driving Car Research Studioの機能車両である QCar は、学術研究用に設計されたオープンアーキテクチャの縮尺モデル車両です。個別に、またはフリートで作業する QCar は、データセットの生成、マッピング、ナビゲーション、機械学習、人工知能、およびその他の高度な自動運転の概念を検証するための理想的な手段です。

ご興味ある方は是非下記の『PRODUCT INFO SHEET』を参照ください。

製品詳細

Dimensios	39 x 19 x 20 cm
Weight (with batteries)	2.7 kg
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	4 GB LPDDR3-1600 RAM 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
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