MicroROS V2 ROS2 AI Robot Car for PC virtual machine (MacOS is not supported)

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MicroROS-V2

MicroROS V2 Robot is an intelligent mobile robot platform specifically designed for ROS2 teaching, robot development, and AI applications. It innovatively adopts a distributed architecture of "PC virtual machine + ESP32 + MicroROS," eliminating the need for expensive mainframes like Raspberry Pi and Jetson, enabling complete ROS2 development and significantly reducing learning costs.

Leveraging MicroROS technology, the robot car can transmit sensor data from LiDAR, camera, and other sources to the PC-based ROS2 system in real time, enabling functions such as SLAM mapping, autonomous navigation, road network planning, and AI visual recognition. Furthermore, the product integrates the OpenClaw intelligent agent framework and a large AI multimodal large language model, supporting natural language interaction and agent application development, providing developers with a complete learning platform from robot control to AI applications.

Cost-Effective ROS2 & MicroROS Learning

No need expensive Jetson or Raspberry Pi control board. Only need use a Windows PC (macOS is not supported) to run the ROS2 environment while MicroROS handles communication with the robot. This architecture significantly reduces the cost of learning ROS robotics, making it ideal for students, educators, laboratories, and robotics beginners.

SLAM Mapping, Autonomous Navigation & Road Network Planning

Equipped with a TOF LiDAR, it supports real-time SLAM mapping, autonomous localization, path planning, and road network planning. Users can build maps and plan navigation routes, achieving a more intelligent and efficient autonomous robot navigation experience.

AI Visual Recognition and Real-time Image Transmission

The standard and superior versions include 2MP WiFi camera module, supporting AI vision applications such as OpenCV vision development, object recognition, color recognition, and visual tracking, enabling robots to possess environmental perception and intelligent interaction capabilities.

AI Agents and Large Language Model Applications

Compatible with AI Agent frameworks such as OpenClaw and Dify, it can be combined with large language models to achieve natural language understanding, task execution, and intelligent control, helping learners experience a new way of AI robot development.

Complete curriculum system for quickly master robot development

Yahboom provide many curriculum from ROS2 basics, MicroROS communication, SLAM mapping, visual recognition, AI large language model applications to multi-robot collaboration, helping learners gradually master robot development skills.