N-VIDIA Official Partner Product

JetRacer AI Kit Professional Version

It meets the needs of scientific research algorithm verification in various fields such as Lidar mapping, autonomous navigation, autonomous driving, intelligent speech, target detection, face recognition, etc. It is not only compatible with software of the N-VIDIA JetRacer open-source project, but also is overall upgraded in hardware with better performance.

* Note: This product provides three options: Kit A, Kit B and Accessories Pack. Jetson Nano Dev Kit is different in Kit A and Kit B, and is not included in the Accessories Pack. Please refer to the part list for detailed package content.

Jetson Nano Developer Kit (B01)
Jetson Nano Developer Kit (B01) is the official N-VIDIA kit with a variety of onboard interfaces including the 40PIN GPIO expansion header, Gigabit Ethernet port, USB 3.0 ports, HDMI port, DIS port and CSI camera connector. The B01 kit onboard is a non-production specification Jetson Nano module, mainly for development and software testing

 

Waveshare Jetson Nano Dev Kit
Waveshare Jetson Nano Dev Kit is the alternative solution of B01 kit, with the Jetson Nano B01 eMMC version module and the Waveshare JETSON-IO-BASE-A carrier board, providing almost the same performance and appearance as the Jetson Nano Developer Kit (B01). The Jetson Nano B01 eMMC version is more suitable for users to integrate in production environments.

The host controller adopts Jetson Nano Dev Kit, provides two version options: N-VIDIA Jetson Nano Developer Kit (B01) and Waveshare Jetson Nano Dev Kit. Both kits have almost the same performance and appearance, except that the Waveshare Jetson Nano Dev Kit adopts a 16GB eMMC version of the Jetson Nano Module. The Jetson Nano Dev Kit is equipped with 4GB memory and has better performance, responsible for Artificial Intelligence (AI), speech processing, visual processing, mapping and navigation, etc.

The sub-controller uses the Raspberry Pi RP2040 dual-core microcontroller, which has better real-time performance and higher control accuracy, and is responsible for attitude data collection and motion control.

Adopting USB Communication, Faster Transmission Speed Than The UART

Deep Learning   Self Driving Car

DonKeyCar utilizes deep learning neural network framework Keras/TensorFlow, together with computer vision library OpenCV, to achieve self driving.

Integrates OpenCV Vision Library, With Extensive Algorithm Demos

AR Vision

 

Face Detection

 

Object Tracking

 

Color Recognition

 

Motion Detection

 

Vision Line Tracking

 

Contour Detection

 

Image Calibration

Supports Remote Speech Intercom, Speech Synthesis, Speech Detection, Speech Recognition, Human-Computer Speech Interaction

High-Quality Carbon Brushes, All-Metal Gear Structure, High Precision, Low Running Noise, 11-Wire AB-Phase Hall Speed Encoder, Support PID Closed-Loop Speed Control To Calculate Wheel Odometer Information

Built-In High-Precision 9-Axis Motion Attitude Sensor, Using Extended Kalman Filter To Merge Wheel Odometer And IMU Data, Can Produce Higher-Precision Robot Attitude

JetRacer ROS AI kit adopts an Ackerman-like steering structure with front wheels servo steering combined with rear wheels differential steering. Provides detailed kinematics model analysis, uses polynomial fitting to output steering angle, makes the steering angle more accurate.

360-Degree Scanning And Ranging Of The Surrounding Environment To Obtain A Contour Map Around The Robot

IMX219 Sensor, 3280 × 2464Resolution
Suitable For OpenCV Vision Development, Object Recognition, Target Tracking, Automatic Driving And Other AI Functions

Onboard Two High-Quality MEMS Silicon Microphones And Speaker For Stereo Recording And Playback. So The Robot Also Has "Ears" And "Mouths" That Can "Listen" And "Talk". Easily Realize Intelligent Speech Interaction

Onboard battery protection circuit for preventing overcharge, over-discharge, overcurrent, short circuit proof, with reverse proof, and equalizing charge. Makes your operation more stable and safer. Built-in battery detection circuit, onboard OLED to real-time display the battery voltage, current, and remaining battery capacity.