As robotics education and AI research continue to evolve, developers, educators, and makers are increasingly looking for platforms that balance performance, flexibility, and long-term scalability.
Based on community adoption, educational demand, and ongoing development trends observed in 2025, the following Yahboom robotics kits are positioned to play a key role heading into 2026.
1.ROSMASTER X3 PLUS ROS Robot
Overview
ROSMASTER X3 PLUS is an omnidirectional movement robot developed based on the ROS robot operating system. It supports four contollers: Jetson NANO 4GB/Jetson Orin NX SUPER/Orin NANO SUPER and Raspberry Pi 5. Equipped with high-performance hardware configurations such as lidar, depth camera, 6DOF robotic arm, 520 high-power motor, voice recognition interactive module, and HD 7-inch display screen. It can realize applications such as APP mapping and navigation, automatic driving, human feature recognition, moveIt robotic arm simulation control and multi-machine synchronous control. It supports mobile phones, handles, computer keyboards remote control. Many video tutorials with Chinese and English subtitles and codes are provided for free.
🔗 Tutorial:
http://www.yahboom.net/study/ROSMASTER-X3-PLUS
🎥 Video:
2.ROSMASTER X3 ROS2 AI voice interaction Robot with Mecanum Wheel
Overview
ROSMASTER X3 is an educational AI voice interaction robot based on the robot operating system with Mecanum Wheel, compatible with Jetson NANO/Orin NX SUPER/Orin NANO SUPER and Raspberry Pi 5. It is equipped with lidar, depth camera, voice interaction module and other high-performance hardware modules. Using Python programming, ROSMASTER X3 can realize mapping and navigation, following or avoiding, Autopilot and human body posture detection. It support APP remote control, APP mapping navigation, handle remote control, ROS2 system PC control and other cross-platform remote control methods. We provide 103 video courses and a large number of codes, which can allow users to learn artificial intelligence programming and ROS systems.
🔗 Tutorial:
https://www.yahboom.net/study/ROSMASTER-X3
🎥 Video:
3.Raspbot V2 AI Large Model Robot Car for Raspberry Pi 5
Overview
RASPBOT-V2 is an AI larger model robot car with a metal body bracket. It is equipped with Mecanum wheels to achieve 360° omnidirectional movement. Raspberry Pi 5 as the main control, Python as programming language. 1MP USB camera and 2DOF PTZ, combining with OpenCV image processing library and MediaPipe machine learning framework to realize color recognition, target tracking, license plate recognition, visual tracking, face recognition, gesture recognition, etc.
🔗 Tutorial:
https://www.yahboom.net/study/RASPBOT-V2
🎥 Video:
4. DOFBOT Pro AI Large Model 3D Depth Vision Robotic Arm
Overview
DOFBOT PRO is a desktop-level 3D AI Large Model and vision robotic arm. Equipped with a series of high-performance hardware such as 3D depth camera, 6-DOF joint, NVIDIA Jetson series board, 10.1-inch touch screen, etc. By integrating ROS robot operating system and forward/inverse kinematics algorithms, the complex motion control of the 6-DOF robotic arm is simplified. We integrate 3D vision technology into robotic arm control to realize depth ranging, shape recognition, height measurement, volume calculation and other functions. Based on these data,DOFBOT PRO can accurately identify, track and grab objects in 3D space.
🔗 Tutorial:
http://www.yahboom.net/study/DOFBOT-Pro
🎥 Video:
5.12DOF AI Large Model Robot Dog DOGZILLA S1/S2 for Raspberry Pi 5(ROS2-HUMBLE)
Overview
DOGZILLA is a visual AI robot dog with 12 degrees of freedom, mainly composed of 6 servos, aluminum alloy brackets, and a camera. It can flexibly complete a series of bionic actions and achieve omni-directional movement and six dimensional attitude control. DOGZILLA is equipped with IMU and servo angle sensors, which can provide real-time feedback on its own posture and joint angles. With inverse kinematics algorithms, achieves various motion gaits. Raspberry Pi as its main controller, with additional configurations such as lidar and voice module. Through Python programming, based on the ROS2 system, many functions such as AI visual recognition, lidar mapping navigation, and voice control can be achieved.
🔗 Tutorial:
http://www.yahboom.net/study/DOGZILLA
🎥 Video:
6.JetCobot 7-axis visual collaborative robotic arm
Overview
JetCobot is a 7-axis visual collaborative robotic arm. It uses the NVIDIA series development board as the main control board. It adopts a configuration similar to the UR robot, flexible movement, and maximum effective arm span of 270MM. Through the ROS robot operating system and inverse kinematics algorithm, the robotic arm coordinate control, motion planning, gripping and sorting functions are realized. It equipped it with a 0.3MP USB camera, combined with OpenCV images, machine vision, deep learning and other algorithms, can complete color interaction, face tracking, label recognition, model training, gesture interaction and other functions. In addition to supporting MoveIt simulation control, JetCobot also supports handle, PC web control.
🔗 Tutorial:
https://www.yahboom.net/study/JetCobot
🎥 Video:
7.Rider-Pi Two Wheel-legged Robot(Raspberry Pi CM5 core module)
Overview
Rider-Pi is a desktop two wheel-legged robot designed for developers, educators and robot enthusiasts. Built-in inertial measurement unit (IMU) and the carbon fiber connecting rod structure, which allow the robot to adjust the joint angle in real time to adapt to different terrain obstacles. Based on the Raspberry Pi CM5 core module, adopt Python programming, support a series of AI functions such as face recognition, color tracking/following, QR code motion control, object detection, license plate recognition, gesture following, etc. A 2.0-inch IPS screen on the front, can display video images and 35 dynamic expressions in real time. In addition, Rider-Pi also supports ChatGPT (extra charge), which can realize voice Q&A, voice control, text-to-picture, and image analysis description functions.
🔗 Tutorial:
https://www.yahboom.net/study/Rider-Pi
🎥 Video:
8.MicroROS-Pi5 ROS2 Robot Car for Raspberry Pi 5 (ROS2-HUMBLE + Python3)
Overview
This MicroROS-Pi5 ROS2 car is developed based on Raspberry Pi 5. It consists of a Micro ROS robot expansion board with ESP32 co-processor, 4PCS 310 encoder motor, high-quality tires, 7.4V 2000mAh rechargeable battery, MS200 lidar, 2MP camera, 2DOF gimbal and an aluminum alloy frame. It adopt ROS2-HUMBLE development environment and Python3 programming, and uses OpenCV image processing and MediaPipe machine learning algorithms to achieve multiple functions such as robot motion control, AI visual interaction, SLAM mapping navigation, RViz simulation and multi-machine synchronization control. Users can control it by mobile APP, wireless controller, computer keyboard control. Yahboom will provide each customer with detailed tutorial materials, installation videos and professional technical support.
🔗 Tutorial:
http://www.yahboom.net/study/MicroROS-Pi5
🎥 Video:
9.ROSMASTER M1 AI Large Model ROS2 Robot with Mecanum Wheel
Overview
ROSMASTER M1 can be equipped with various peripherals, including a 3D depth camera/2MP HD camera PTZ(optional), LiDAR, AI voice module, and ROS robot expansion board, building human-level 3D visual perception and environmental understanding capabilities. It supports Raspberry Pi 5, RDK X5, Jetson Nano 4GB, and Jetson Orin Nano 8G, and is fully compatible with ROS2 HUMBLE, deeply integrating with mainstream AI frameworks. Employing an innovative multimodal dual-model collaborative reasoning architecture, it efficiently integrates visual, voice, and text information, possessing human-like capabilities such as continuous dialogue, instant interruption, dynamic scene reasoning, and intentions speculation.
Whether conducting SLAM mapping and navigation, AI visual recognition, path planning research, or carrying out multimodal human-computer interaction experiments, this robot car can meet all your needs.
🔗 Tutorial:
https://www.yahboom.net/study/ROSMASTER-M1
🎥 Video:
10.Yahboom DOFBOT AI Vision Robotic Arm with ROS Python programming
Overview
DOFBOT is the best partner for AI beginners, programming enthusiasts and Jetson nano fans. It is designed based on Jetson NANO 4GB and contains 6 HQ servos, a HD camera and a multi-function expansion board. The whole body is made of green oxidized aluminum alloy, which is beautiful and durable. Through the ROS robot system, we simplify the motion control of serial bus servo. We adopt Open Source CV as the image processing library and Python3 programming language to create a series of AI visual game play. For example, color tracking, color interaction, garbage classification, gesture recognition, face tracking, etc. And it can be controlled by Android/iOS mobile APP, PC computer and game handle. In addition, we will provide some tutorials for reference.
🔗 Tutorial:
http://www.yahboom.net/study/Dofbot-Jetson_nano
🎥 Video:
Conclusion
These ten Yahboom robotics kits represent not just current popularity, but strong alignment with the skills, technologies, and learning paths that will define robotics development in 2026. Whether you’re an educator, student, or researcher, these platforms offer a reliable foundation for building the next generation of intelligent systems.
Explore, learn, and build with Yahboom—today and beyond. https://category.yahboom.net/