JetRacer ROS AI Robot
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: NVIDIA Jetson Nano has been officially announced as End-of-Life (EOL) starting January 2026. Long-term availability, future software updates, and extended support will be limited.
| JETRACER KIT | JETRACER ROS KIT | |
|---|---|---|
| APPEARANCE |  |
 |
| MICROCONTROLLER | N/A | Raspberry Pi RP2040 Chip |
| MOTOR | 37-520 DC Gear Motor Reduction rate 1:10 Idle speed 740RPM |
37-520 Metal Encoder Motor Reduction Rate 1:30 Idle Speed 333RPM |
| MOTOR ENCODER | N/A | 11 wire AB phase hall speed sensor, supports wheel odometry |
| IMU SENSOR | N/A | MPU9250 |
| LIDAR | N/A | RPLIDAR A1 |
| AUDIO INTERFACE | N/A | One Speaker, Dual Microphones, Support Intelligent speech |
| MAPPING NAVIGATION | Not Support | Support |
Intelligent Dual-Controller Design
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
Developed Based On ROS
ROS (Robot Operation System) is an open-source operating system that includes a collection of software libraries and tools for robot design. It provides the services expected of an operating system, including hardware abstraction, bottom layer device control, implementation of common functions, message transfering between processes, and package management. ROS simplifies robot design and is the mainstream robot software framework in the world.
Support I2C Slave Mode Control
Completely Compatible With Original JetRacer Demo
Jetracer ROS AI Kit is an autonomous Al racing car powered by N-VIDIA Jetson Nano. By interactive programming via web browser, it allows high frame rate processing due to torch2trt (PyTorch to TensorRT translator) optimizing, so that faster autonomous line following driving can be easily achieved.
High School AI Education, Race-Specified Intelligent Car
DonKeyCar Open Source Project
Deep Learning | Self Driving Car
DonKeyCar utilizes deep learning neural network framework Keras/TensorFlow, together with computer vision library OpenCV, to achieve self driving.
SLAM Lidar Mapping
Mapping With Odometer, IMU, Lidar, EKF, Etc.
Supports Gmapping, Hector, Karto, And Cartographer Mapping Algorithms
Path Planning, Autonomous Navigation,
Dynamic Obstacle Avoidance
Adaptive Monte Carlo Localization (AMCL) | Move_base Autonomous Navigation
Supports Single-Point Navigation, Multi-Point Patrol Navigation, And Mapping While Navigating
Single-point Navigation
After publishing the navigation target position, the robot will automatically plan the path to navigate to the target position.
Multipoint Patrol Navigation
Add navigation dots, the robot will cruise and navigate between the navigation dots.
Mapping while navigating
After publishing the navigation target position, the robot will automatically explore the path to the target point, and publish it while scanning the map.
OpenCV Vision Processing
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 |
Intelligent Speech Processing, Human-Robot Speech Interaction
JetRacer ROS AI Robot
SKU: ROBO215
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JetRacer ROS AI Robot
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: NVIDIA Jetson Nano has been officially announced as End-of-Life (EOL) starting January 2026. Long-term availability, future software updates, and extended support will be limited.
| JETRACER KIT | JETRACER ROS KIT | |
|---|---|---|
| APPEARANCE | |
|
| MICROCONTROLLER | N/A | Raspberry Pi RP2040 Chip |
| MOTOR | 37-520 DC Gear Motor Reduction rate 1:10 Idle speed 740RPM |
37-520 Metal Encoder Motor Reduction Rate 1:30 Idle Speed 333RPM |
| MOTOR ENCODER | N/A | 11 wire AB phase hall speed sensor, supports wheel odometry |
| IMU SENSOR | N/A | MPU9250 |
| LIDAR | N/A | RPLIDAR A1 |
| AUDIO INTERFACE | N/A | One Speaker, Dual Microphones, Support Intelligent speech |
| MAPPING NAVIGATION | Not Support | Support |
Intelligent Dual-Controller Design
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
Developed Based On ROS
ROS (Robot Operation System) is an open-source operating system that includes a collection of software libraries and tools for robot design. It provides the services expected of an operating system, including hardware abstraction, bottom layer device control, implementation of common functions, message transfering between processes, and package management. ROS simplifies robot design and is the mainstream robot software framework in the world.
Support I2C Slave Mode Control
Completely Compatible With Original JetRacer Demo
Jetracer ROS AI Kit is an autonomous Al racing car powered by N-VIDIA Jetson Nano. By interactive programming via web browser, it allows high frame rate processing due to torch2trt (PyTorch to TensorRT translator) optimizing, so that faster autonomous line following driving can be easily achieved.
High School AI Education, Race-Specified Intelligent Car
DonKeyCar Open Source Project
Deep Learning | Self Driving Car
DonKeyCar utilizes deep learning neural network framework Keras/TensorFlow, together with computer vision library OpenCV, to achieve self driving.
SLAM Lidar Mapping
Mapping With Odometer, IMU, Lidar, EKF, Etc.
Supports Gmapping, Hector, Karto, And Cartographer Mapping Algorithms
Path Planning, Autonomous Navigation,
Dynamic Obstacle Avoidance
Adaptive Monte Carlo Localization (AMCL) | Move_base Autonomous Navigation
Supports Single-Point Navigation, Multi-Point Patrol Navigation, And Mapping While Navigating
Single-point Navigation
After publishing the navigation target position, the robot will automatically plan the path to navigate to the target position.
Multipoint Patrol Navigation
Add navigation dots, the robot will cruise and navigate between the navigation dots.
Mapping while navigating
After publishing the navigation target position, the robot will automatically explore the path to the target point, and publish it while scanning the map.
OpenCV Vision Processing
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 |