In the era of rapid technological development, robotics has become an indispensable part of the education field. In particular, ROS (Robot Operating System), as an open source robot operating system, not only provides a powerful development environment for developers, but also provides students and educational institutions with many learning resources and tools. With the continuous development of ROS educational robots, more and more high-quality ros robot kits are being launched, suitable for students and educators of different ages.
In this article, I will recommend 9Â most noteworthy ROS educational robot kits in 2025. These robots not only have excellent technical performance, but also can help students better master knowledge in robotics, artificial intelligence, and programming.
ROSMASTER X3
As the best-selling product among all Yahboom ROS educational robots, ROSMASTER X3 is loved by users from all over the world. From 2022 to 2025, ROSMASTER X3 has completed 4 version updates. Equipped with high-quality accessories such as Mecanum wheels, SLAM lidar, Orbbec depth camera, voice interaction module, etc., based on the ROS2 development environment, Yahboom have designed and developed 3D visual mapping navigation, MediaPipe development, voice interaction, multi-machine synchronous control and other functions.
Features
1) Suspendable chassis structure, Mecanum wheels support 360° omnidirectional movement.
2) Support Jetson NANO 4GB B01, Jetson ORIN NANO, Jetson ORIN NX and Raspberry Pi 5 as the main control.
3) Complete support ROS2, suitable for learning the latest version of ROS.
4) High-precision sensors such as lidar, depth camera, voice interaction module, etc.
5)Â Rich learning resources, suitable for various learning needs from beginners to advanced developers.
Applicable people
Those who need to achieve omnidirectional mobility, and are suitable for students, developers and educators who want to gain a deeper understanding of robotics technology, especially the ROS2 system.
Tutorisla link
Yahboom ROMASTER X3 ROS2 ROBOT Kit
ROSMASTER R2
ROSMASTER R2 car adopts Ackerman steering structure and is designed and developed based on ROS2 system. It supports Jetson series boards and Raspberry Pi 5 board as the main control, and can meet the power supply requirements of the corresponding development boards. It is equipped with high-quality hardware such as laser lidar, depth camera, voice interaction module, etc., providing powerful functions, including robot motion control, remote control communication, map navigation, obstacle avoidance and following, autopilot, human feature motion recognition, voice interaction control and other application scenarios. This car is equipped with many learning courses, allowing users to easily master ROS and play with robot technology from entry to advanced.
 
Features
1) The chassis adopts Ackerman steering structure, which is specially designed for autonomous driving.
2) Compatible with Jetson NANO 4GB B01, Jetson ORIN NANO, Jetson ORIN NX and Raspberry Pi 5.
3) Equipped with competition-specific rubber tires, 520 motors (550RPM (1:19)), SLAMÂ A1/YDLIDAR 4ROS lidars, depth cameras, etc.
4) Supports multiple remote control methods: mobile phone APP, wireless handle, ROS operating system, computer keyboard, etc.
Applicable people
Suitable for robotics enthusiasts, educators and developers, especially students interested in autopilot of smart cars.
Tutorisla link
Yahboom ROMASTER R2 ROS2 ROBOT Car with Ackermann structure
MicroROS Self-balancing Robot Car
The MicroROS two-wheeled self-balancing car is a robot platform based on the MicroROS (Lightweight version ROS) system, designed for educational and research applications. It uses advanced 6-axis attitude sensors to achieve precise two-wheeled self-balancing functions. The car is equipped with ESP32+STM32 dual processors, 520 high-power motors, TOF laser lidars, and ROS-WiFi camera modules. While ensuring efficient drive motors to maintain balance, it can also transmit lidar, motor, and gyroscope data to the virtual machine through MicroROS wireless communication technology, complete relevant data processing, and send corresponding commands to the car.
Features
1) With the help of gyroscopes and accelerometers, accurate self-balancing control can be achieved, and the stability of the car can be guaranteed whether it is stationary or moving.
2) Supports 4KG load, 30° climbing, and ultrasonic obstacle avoidance.
3) Developed using the MicroROS system, data is transmitted through wireless communication technology, and the virtual machine is used as the main control. Without additional main control board, which greatly reduces the user's learning cost.
4) Modular design for easy assembly and debugging. With the addition of TOF lidar, WiFi camera and other modules, it can easily achieve obstacle avoidance, automatic navigation, real-time video transmission, AI visual recognition and other functions.
Applicable people
Suitable for ROS2 beginners with limited budget;
Students in educational institutions learn robotics, control systems, embedded development and sensor fusion technologies.
Tutorisla link
Yahboom MicroROS self-balancing car
JetCobot
JetCobot is designed based on MyCobot280 and is a high-precision, multifunctional 7-DOF robotic arm. We equipped it with a USB high-definition camera module and NVIDIA Jetson series development board to achieve a combination of robotic arm control and visual recognition. It can accurately identify objects such as color, face, and human posture. By calculating the position of the object through geometric relationships, the robotic arm can accurately locate, grasp, track, and other actions.
Features
1) Adopting a 7-axis design, the configuration is similar to that of the UR robot, and with the inverse kinematics algorithm, it ensures flexible and accurate motion control, with a maximum effective arm span of 270MM and a joint rotation range of -153°~153°, which can handle a variety of complex operation tasks.
2) Equipped with a 0.3MP USB camera and a field of view of 110°. Combined with OpenCV image processing, machine vision, and deep learning algorithms, JetCobot can realize color interaction, face tracking, label recognition, model training, gesture interaction, and other functions.
3) With the NVIDIA series development board as the main control, JetCobot has powerful computing power and AI processing capabilities, which can efficiently process complex visual and control algorithms to ensure real-time response and efficient execution.
4) Based on the ROS robot operating system, JetCobot can realize MoveIt simulation control, and also supports APP control (only for Android), handle control and PC webpage control to meet the needs of different users.
Applicable people
Product developers and researchers of enterprises use JetCobot as a prototype development platform for intelligent robot products to test and implement various applications related to robot vision, control and automation, laying the foundation for actual product development and commercialization.
Suitable for robot technology research, intelligent control algorithm verification and robot vision system development in the laboratory.
Tutorisla link
Yahboom Jetcobot educational robotic arm kit
Muto RS
Muto RS is a desktop-level 18-DOF bionic hexapod robot, developed and designed based on ROS2, and compatible with Jetson NANO and Raspberry Pi. The overall body is made of aluminum alloy, containing 35KG serial bus servo, depth camera, laser lidar, and voice module. Through Python3 programming and built-in high-precision algorithms, Muto RS can easily realize AI visual interaction, 3D mapping navigation, voice interaction, deep learning, and Rviz simulation. Based on multi-machine communication technology, we can also let Muto complete multi-machine synchronous control and multi-machine navigation, and users can control it through APP, wireless handles, computer web pages, etc.
Features
1) Contains 18PCS 35KG metal bus servo, depth camera, laser lidar, voice interaction module, large-capacity battery and other high-quality accessories, providing Muto RS with more stable performance.
2)Â Compatible with Raspberry Pi and Jetson NANO, using Python3 programming, ROS2 operating system and inverse kinematics algorithm to accurately control robot movement.
3) Easily realize 3D mapping navigation, voice interaction, synchronous control, deep learning, visual recognition, docker container development, laser lidar tracking and obstacle avoidance and other functions.
4)Â Yahboom provides multi-function remote control APP, wireless controller, mapping navigation APP, so that users can control Muto RS anytime and anywhere.
5)Â Support RVIZ simulation, users can control robots and verify algorithms in a virtual environment.
Applicable people
Individual developers interested in bionic robots and robot control systems.
Suitable for players or teams in robot competitions and robot challenges, Muto RS provides high-precision control and rich functions, especially in the motion control and visual interaction of bionic robots. It has significant advantages, which can help contestants gain competitive advantages in precise grasping, navigation, recognition and other aspects.
Tutorisla link
Yahboom 18DOF Muto RS Hexapod Robot
Transbot-SE
TRANSBOT-SE is a tracked tank car with a 3DOF robotic arm. It is compatible with Jetson Nano B01 and Raspberry Pi 5 main control boards and is developed based on the ROS system. A 2DOF camera PTZ is installed in front of the car, which can be used to collect video images to realize AI visual recognition functions. Through Python programming, plus built-in OpenCV image processing algorithms, MediaPipe machine learning, AI deep learning framework, and movelt simulation platform, it can realize robot motion control, robotic arm handling, remote control communication, intelligent AI recognition, tracking, automatic driving, robotic arm simulation control and other functions.
Features
1) Tracked structure, the whole vehicle is made of aluminum alloy, equipped with HQ tracks and high-power motors.
2) 2DOF 2MP camera, combined with APP or remote control handle, can realize real-time video transmission.
3) 3DOF robotic arm, not only can realize the grabbing and handling function of the robotic arm, but also can realize MoveIt simulation.
4) Based on ROS operating system, using Python programming, supporting Jetson Nano B01 and Raspberry Pi 5.
5) Through OpenCV image processing and MediaPipe framework, a series of functions related to AI visual recognition are realized.
Applicable people
Suitable for beginners who have just entered ROS robot development. Technicians engaged in embedded system development. This product supports Jetson Nano B01 and Raspberry Pi 5, providing a powerful hardware platform for embedded development. Developers can perform system integration, programming control and robot function expansion.
Tutorisla link
Yahboom Transbot SE educational Tank car
DOGZILLA
DOGZILLA is a desktop-level bionic robot dog with 12 degrees of freedom, mainly composed of 6PCS servos, aluminum alloy brackets and a camera. It is equipped with lMU and joint position sensors, which can feedback its own posture, joint rotation angle and torque. The coprocessor combines the inverse kinematics algorithm to achieve various motion gaits and superposition effects. Using Raspberry Pi 5 as its main controller, based on the ROS2 operating system, through Python programming, it can realize AI visual recognition, lidar mapping navigation, voice control and other functions.
Features
1) Can walk and twist like a real dog.
2)Â Equipped with 6 high-precision servo motors, aluminum alloy body, wide-angle camera. The S2 version adds lidar and voice interaction modules.
3)Â Using Raspberry Pi as the master control, we upgraded the ROS2 system to support Python programming and RVIZ simulation.
4)Â Supports multiple remote control methods such as APP, handle, web page, computer keyboard, APP map navigation, etc.
5) S1/S2 is easily completed based on ROS2 and OpenCV, and has functions such as tag recognition, face detection, target tracking, and visual line patrol.
6) S2 comes with a laser lidar and intelligent voice module, which can realize map navigation, laser lidar obstacle avoidance and following, voice control and other functions.
Applicable people
Personal developers interested in bionic robots and robot control systems.
Scientists engaged in robotics, artificial intelligence, computer vision and embedded systems research.
Tutorisla link
Yahboom 12DOF Robot Dog DOGZILLA S1/S2
DOFBOT-PRO
This 3D depth vision robotic arm is designed based on the NVIDIA Jetson series development board. The robotic arm is equipped with high-performance hardware such as 3D depth camera, 6-DOF motion joint, NVIDIA Jetson master control, 10.1-inch touch screen, voice module, etc. It supports ROS system, is compatible with multiple operating platforms, and provides flexible control and programming functions. It can not only realize depth distance measurement, shape recognition, height measurement, and volume measurement, but also can identify and track, grab target objects in three-dimensional space through the robotic arm, and realize some image recognition tasks.
Features
Based on NVIDIA Jetson series boards, higher computing power and smoother operation. DOFBOT PRO is compatible with Jetson NANO 4GB/Jetson Orin NANO/Jetson Orin NX boards. It trains machine learning models through the GPU of the Jetson board, and uses python programming and depth learning frameworks. It is jointly developed with MediaPipe to realize AI creative projects such as object image recognition, gesture control, and human posture recognition.
Deep point cloud recognition, three-dimensional space grasping.
Combined with a high-performance 3D depth camera, DOFBOT-PRO can not only realize environmental perception, object recognition and other functions, but also perform accurate 3D spatial positioning according to the target RGB data, position coordinates and depth information, and combine RGB+D fusion detection to complete complex visual recognition and grasping tasks.
6-DOF structural design, aluminum alloy material.
The entire robot body is made of high-quality aluminum alloy and has six flexible degrees of freedom. Each joint uses a high-precision servo, which has a faster response speed and can perform smooth multi-axis movement.
Multiple cross-platform remote control methods.
DOFBOT PRO supports APP (Android/iOS), wireless handles, and PC web page control, allowing you to control the robot as you wish.
Applicable people
Individuals who are interested in robot development and control can use this platform for independent design and innovation. Suitable for teaching robotics and artificial intelligence courses in middle schools and universities to help students practice and deepen their understanding of robotics technology.
Used for robot research and verification of the forward and inverse kinematics algorithms of the robot. Developers and makers who want to use the robot as an open source platform for secondary development and product prototyping.
Tutorisla link
Yahboom DOFBOT-PRO 3D Depth robotic arm
RDK X3 ROS ROBOT
RDK ROBOT is developed based on ROS2 and TogetherROS robot operating system. It is equipped with RDK X3/X5 motherboard, Mecanum wheel, LiDAR, HD camera/depth camera and other accessories. Through Jupyter Lab, Python language programming and development can realize visual line patrol, human tracking, gesture control, color tracking, radar mapping navigation and obstacle avoidance and other functions.
Features
Powerful computing power
Adopting the new RDK X3/RDK X5 development board, it has sufficient computing resources to process real-time data and complex computing tasks. Combining Python programming and ROS2 operating system, users can develop various intelligent algorithms.
Cost-effective hardware configuration
The car is equipped with Mecanum wheel, depth camera, TOF LiDAR, which can realize mapping navigation, intelligent obstacle avoidance, gesture control, sight inspection and other functions.
Support multiple remote control methods
Users can control the car through mobile phone APP, PS2 handle, computer keyboard, ROS operating system, etc., and we have also developed a mapping navigation APP for it, so that users can realize mapping navigation at any time.
Aluminum alloy structure, stacking structure
The RDK robot car is made of white sandblasted aluminum alloy, with a stacking structure inside. All connecting wires are cleverly stored, making the car look beautiful and neat.
Applicable people:
Students who need to achieve omnidirectional mobility and want to learn ROS2 system development.
As a training and development platform for robot competitions, it helps players to prepare for competition projects such as path planning, automatic navigation, and multi-robot collaboration.
Maker teams and start-ups that have a demand for innovation and technology research and development. This kit can provide them with a suitable development platform to support hardware development, algorithm debugging and system testing, and help product development, technology verification and prototype design.
Tutorisla link
Conclusion
In 2025, with the rapid advancement of robotics technology, ROS educational robot kits have become an indispensable tool in teaching, scientific research, and practical application development. From beginners to professional developers, these kits provide a complete platform to help users deeply understand the working principles of the Robot Operating System (ROS) and master robot programming and control technology. In this article, we introduce the 9 most recommended ROS educational robot kits in 2025, each of which has unique features and advantages for different learning needs and application scenarios.
These robot kits not only support a wide range of development environments and programming languages, but also are equipped with high-quality hardware to achieve complex functions such as precise motion control, sensor data acquisition, image processing, and machine learning. Whether it is used for basic teaching of robotics or for scientific researchers to develop robot algorithms and systems, these kits can provide strong support. For schools and educational institutions, they are not only a powerful tool for classroom teaching, but also a valuable resource for cultivating students' hands-on ability, innovative thinking, and practical ability.
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