Weight: 1.646 kg
JetRacer Professional Version ROS AI Kit, Dual Controllers AI Robot, Lidar Mapping, Vision Processing
JetRacer ROS AI Robot
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.
Ordering Options
* Waveshare Jetson Nano Dev Kit is included in the Full Kit
Intelligent Dual-Controller Design
The host controller adopts Waveshare Jetson Nano Kit, which is equipped with Jetson Nano Module 16GB eMMC version, 4GB memory and has better performance. This controller is 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
Supports Remote Speech Intercom, Speech Synthesis, Speech Detection, Speech Recognition, Human-Computer Speech Interaction
Real-Time Remote Speech Transmission, Allowing Robots To Deliver Conversations
Real-Time Speech Transmission Between The Computer And The Robot, Enables Two-Way Remote Communication
Speech Synthesis Playback, Let The Robot Speak
Convert Text To Natural, Smooth Vocals And Play
Send A Text Topic To The Robot, And You Can Hear It Talking
Speech Detection, Let The Robot Know I'm Speaking
Detects The Sound Of The Audio Stream And Removes The Mute Part
Only Take The Part That The Person Speaks
Speech Recognition, Let The Robot Understand What I Say
Recognize Audio As Text
Block Diagram
High-Power Encoder DC Gear Motor
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
IMU Sensor
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
Adopts Ackerman-Like Steering Structure
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 Laser Ranging Lidar
360-Degree Scanning And Ranging Of The Surrounding Environment To Obtain A Contour Map Around The Robot
8MP 160 FOV Camera
IMX219 Sensor, 3280 × 2464Resolution
Suitable For OpenCV Vision Development, Object Recognition, Target Tracking, Automatic Driving And Other AI Functions
Using USB Audio Chip
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
Safe & Stable Circuit Design
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.
Product Structure
Highly Integrated Expansion Board
Packaging Show
Dimensions
Resources & Services
Wiki: www.waveshare.com/wiki/JetRacer_ROS_AI_Kit
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