Product Portfolio
We provide professional embodied robotics solutions for education and research. Our portfolio brings together seven core products spanning introductory teaching through advanced research, integrating mechanics, electronics, and AI with flexible expansion options and comprehensive supporting resources. From K12 robotics education and vocational skills training to university teaching and frontier research, each solution is designed to match real-world instructional and research needs.
7 Core Products
From entry-level to advanced, covering K12 through universities and research.
M Series · Modular Learning Platforms
Modular kits for inspirational learning through advanced curriculum design, spanning entry projects to research-grade builds.
Embodied Robot Innovation Design Kit (40-in-1) Ubot MR40
Build 40 typical embodied robot configurations from scratch, covering chassis, robotic arms, and composite robots. Supports graphical programming plus C++ (Arduino) and Python development, with progressive curriculum resources for introductory robotics education, innovation projects, and competition training.
Embodied Robotics Innovation Platform (Enhanced) GX-MAT-09S
Engineering-grade embodied composite robot design kit, supporting the construction of 11 chassis + 7 robotic arms and over 80 composite robot configurations. Uses 12V encoded DC motors with a chassis load capacity up to 25kg. Control covers Arduino, STM32, and edge computing boards, supporting multi-level development and mainstream robot sensors like vision and LiDAR. Suitable for professional innovation training.
P Series · Practical Training Platforms
Task-driven embodied robotics platforms for navigation, perception, planning, and LLM-integrated experiments.
Portable ROS Navigation Learning Platform UNI-WR2
A portable ROS navigation robot under 13 cm in length, designed for desktop SLAM labs in spaces as small as 60×60 cm. Includes a five-step ROS engineering workflow covering Cartographer, Hector, and Gmapping.
Embodied Robot Task Planning Training Platform RAI-P4
An all-in-one training platform for embodied interactive agents, integrating foundation models, voice, vision, robotic arms, and gimbals. Compatible with mainstream models such as DeepSeek, Qwen, and Doubao, and supports OpenCV, YOLO, and multimodal VLM workflows. It includes practical course modules covering agent design from concept to deployment, robot control, agent development, and vision integration for professional university training.
Embodied Composite Robot System Design Training Platform RAI-M4
A one-stop embodied AI training platform integrating an omnidirectional chassis, 5-axis robotic arm, depth camera, LiDAR, and voice interaction. Adapts to mainstream large models like Qwen. Features 3 vision solutions and 2 SLAM navigation solutions. Built-in ROS 2. Equipped with comprehensive courses on embodied agents, vision, navigation, and Robot Operating System. Suitable for professional comprehensive training.
Embodied Robot Manipulation Planning Training Platform ALO-LE4
Dual 5-axis arms. An embodied robot operation and execution training platform based on the ACT architecture end-to-end solution. Ready-to-use out of the box with no deployment required. Can serve as a data collection platform and is also suitable for research on imitation learning and end-to-end intelligent control solutions.
Key Questions
Q1: Which education stages do these products cover, and which core products are recommended for each?
Answer: The products in this document cover all educational stages from K12 and secondary vocational education to higher vocational, undergraduate, postgraduate, and research. Recommended products by stage are as follows:
K12, secondary vocational / first-year higher vocational, and first-year undergraduate: the recommended product is the Embodied Robot Innovation Design Kit (40-in-1) Ubot MR40. It supports graphical programming plus C++ / Python development, has a low assembly threshold, and allows students to build chassis, robotic-arm, and composite-robot configurations from scratch, making it well suited for introductory robotics teaching, exploration, and competition entry;
Undergraduate foundation courses: the recommended product is the embodied robot innovation design platform (enhanced edition) GX-MAT-09S . It supports core courses such as mechanical principles, sensor inspection, and ROS fundamentals, and can build 11 chassis types plus 7 robotic arm configurations, covering classroom experiments and competition training;
Undergraduate advanced courses and postgraduate / research use: the recommended product is the embodied intelligence task planning training platform RAI-P4 . It integrates large-model and robotics technologies and supports research on task planning and speech/vision fusion intelligent systems.
Q2: For university courses in ROS and mobile robot navigation, which products are most suitable and why?Embodied Robotics Innovation Platform (Enhanced) GX-MAT-09SPortable ROS Navigation Learning Platform UNI-WR2
Answer: The most suitable products for ROS and mobile robot navigation courses are the portable ROS navigation robot learning platform UNI-WR2 and the embodied robot innovation design platform (enhanced edition) GX-MAT-09S. Their core advantages are as follows:
UNI-WR2：
• Flexible deployment: ultra-portable (<13 cm, <550 g), enabling SLAM navigation on a tabletop as small as 60 cm × 60 cm without requiring a large site;
• Teaching depth: ROS engineering deployment is broken down into 5 steps (principles → demonstration → framework decomposition → package configuration → full-parameter tuning), combined with Cartographer, Hector, and Gmapping navigation methods to form progressive experiments;
GX-MAT-09S：
• Comprehensive functions: supports ROS courses, can assemble 11 chassis types plus 7 robotic arm configurations, and with the lidar module (range 0.12-8 m) covers mobile robot navigation and localization practice;
• Computing support: equipped with an RDK X5 mainboard (10 TOPS) and preinstalled Ubuntu + ROS, supporting the execution and tuning of complex algorithms such as SLAM mapping and autonomous obstacle avoidance.
Q3: Which products support LLM integration and what can they do?Embodied Composite Robot System Design Training Platform RAI-M4Embodied Robot Task Planning Training Platform RAI-P4Embodied Vision Perception & Decision Training Platform RAI-Q2
Answer: There are three products that support large-model integration:
RAI-P4: integrates Qwen, DeepSeek, and Volcano Engine; supports ASR (Qwen), LLM (DeepSeek), TTS (Volcano Engine), and function calling (such as voice-dialog calculators, music playback, and gimbal / robotic arm task planning), and also supports integrated applications with YOLO, face tracking, and robotic arm control.
RAI-M4: connects to DeepSeek (LLM) and Qwen (ASR + multimodal); supports converting natural language into robot task workflows (voice commands for chassis / robotic arm control) and multimodal object detection (Qwen), combining a mecanum chassis and a 4-axis robotic arm to achieve generalized manipulation.
