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Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano
Load image into Gallery viewer, JetAuto ROS Robot For Jetson Nano

JetAuto ROS Robot for Jetson Nano


Regular price ₹ 84,999.99
Sale price ₹ 84,999.99 Regular price ₹ 94,999.99
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JetAuto is an entry-level ROS robot car tailored for ROS education. It is loaded with NVIDIA Jetson Nano, high-performance encoder motor, rotatable pan-tilt, Lidar, 3D depth camera and 7-inch screen, which opens up more functionalities. Robot motion control, mapping and navigation, path planning, tracking and obstacle avoidance, autonomous driving, human feature recognition, somatosensory interaction and voice interaction all can be achieved!

Diverse combination of the hardware makes JetAuto an ideal platform where you can learn and verify robotic SLAM function, as well as get the solution to ROS development. Massive ROS learning materials and tutorials are provided to help you get started quickly!

Jetson Nano Control System

NVIDIA Jetson Nano is able to run mainstream deep learning frameworks, such as TensorFlow, PyTorch, Caffe/ Caffe2, Keras, MXNet. Provide powerful computing power for massive AI projects. Powered by Jetson Nano, JetAuto can implement image recognition, object detection and positioning, pose estimation, semantics segmentation, intelligent analysis and other almighty functions.

Lidar Functions

2D Lidar Mapping and Navigation

JetAuto is loaded with high-performance Lidar that supports mapping with diverse algorithms including Gmapping, Hector, Karto and Cartographer. In addition, path planning, fixed-point navigation as well as obstacle avoidance amid navigation can be implemented.

Single-point Navigation, Multi-point Navigation

JetAuto employs Lidar to detect the surroundings in real time to achieve single-point navigation as well as multi-point navigation.

TEB Path Planning, Obstacle Avoidance

It supports TEB path planning, and is able to monitor the obstacle in real time during navigation. Therefore, it can replan the route to avoid the obstacle and continue moving.

RRT Autonomous Exploration Mapping

Adopting RRT algorithm, JetAuto can complete exploration mapping, save the map and drive back to the starting point autonomously, so there is no need for manual control.

Lidar Tracking

By scanning the front moving object, Lidar makes robot capable of target tracking.

Lidar Guarding

Guard the surroundings and ring the alarm when detecting intruder.

Depth Camera

RTAB-VSLAM 3D Mapping and Navigation

Depth camera supports 3D mapping in two ways, pure RTAB vision and fusion of vision and Lidar, which allows JetAuto to navigate and avoid obstacle in 3D map, as well as re-locate globally.


ORB-SLAM is an open-source SLAM framework for monocular, binocular and RGB-D cameras, which is able to compute the camera trajectory in real time and reconstruct 3D surroundings. And under RGB-D mode, the real dimension of the object can be acquired.

Depth Map Data, Point Cloud

Through the corresponding API, JetAuto can get depth map, color image and point cloud of the camera.


Deep Learning, Autonomous Driving

With JetAuto, you can design an autonomous driving scenario to put ROS into practice, which enables you to better understand core functions of autonomous driving.

Road Sign Detection

Through training the deep learning model library, JetAuto can realize autonomous driving with AI vision.

Lane Keeping

JetAuto is capable of recognizing the lanes on both sides to maintain safe distance between it and the lanes.

Automatic Parking

Combined with deep learning algorithm, JetAuto can recognize the parking sign, then steers itself into the slot automatically.

Turning Decision Making

According to the lanes, road signs and traffic lights, JetAuto will estimate the traffic and decide whether to turn.

MediaPipe Development, Upgraded AI Interaction

Based on MediaPipe framework, JetAuto can carry out human body recognition, fingertip detection, face detection, 3D detection and more.

Fingertip Trajectory Recognition

Human Body Recognition

3D Detection

3D Face Detection

AI Deep Learning Framework

Utilize YOLO network algorithm and deep learning model library to recognize the objects.

KCF Target Tracking

Relying on KCF filtering algorithm, the robot can track the selected target.

Color/Tag Recognition and Tracking

JetAuto is able to recognize and track the designated color, and can recognize multiple April Tags and their coordinates.

Augmented Reality (AR)

After you select the patterns on the APP, the patterns can be overlaid on the April Tag.

Far-field Microphone Array

This 6-microphone array is adroit at far-field sound source localization, voice recognition and voice interaction. In comparison to ordinary microphone module, it can implement more advanced functions.

Sound Source Localization

Voice Interaction

Voice Navigation

Interconnected Motorcade

Multi-vehicle Navigation

Depending on multi-machine communication, JetAuto can achieve multi-vehicle navigation, path planning and smart obstacle avoidance.

Intelligent Formation

A batch of JetAuto cars can maintain the formation, including horizontal line, vertical line and triangle, during moving.

Group Control

A group of JetAuto can be controlled by only one wireless handle to perform actions uniformly and simultaneously.


ROS Robot Operating System

Global Popular Robotic Communication Framework

ROS is an open-source meta operating system for robots. It provides some basic services, such as hardware abstraction, low-level device control, implementation of commonly used functionality, message-passing between processes, and package management. And it also offers the tools and library functions needed to obtain, compile, write, and run code across computers. It aims at providing code reuse support for robotics research and development.

Gazebo Simulation

JetAuto employs ROS framework and supports Gazebo simulation. Gazebo brings a fresh approach for you to control JetAuto and verify the algorithm in simulated environment, which reduces experimental requirements and improves efficiency.

JetAuto Simulation Control

The kinematics algorithm can be verified in simulation to speed up algorithm iteration and reduce the experiment cost.

Visual Data

RViz can visualize the mapping and navigation result, which facilitates debugging and improving algorithm.

Various Control Methods

WonderAi APP

Map Nav APP (Android Only)

Wireless Handle


Product Structure




ORBBEC Astra Pro Depth Camera


iFLYTEK Far-field Microphone Array Module


HD 7-inch LCD Touch Screen


Intelligent Serial Bus Servo


Core Accessories

Multi-functional Expansion Board

The expansion board has a built-in IMU sensor which can detect robot posture in real time. There are 2-channel PWM, two keys, a LED, a buzzer, 9-channel serial bus servo interface, two GPIO expansion ports and two IIC interfaces on it.

Hall Encoder Geared Motor

520 motor comes with high-accuracy encoder, and features strong force and high performance. The built-in AB phase incremental Hall encoder stands out for its high accuracy and anti-interference ability.

11.1 V 6000mAh Lipo Battery

This large-capacity Lipo battery can better power the robot and prolongs robot’s working life.

Encoder Motor Driver

JetAuto is equipped with 4-channel encoder motor driver making it easier to control motor.


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