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The Yahboom MicroROS Robot Car combines advanced ROS2 AI SLAM mapping and navigation capabilities with AI-powered visual recognition, enhanced by the powerful ESP32 AI Module. Designed for hobbyists and developers who want cutting-edge robotics solutions, this AI Vision Edition enables seamless interaction with virtual machine software. Please note, VM software compatibility excludes Mac systems.
Experience advanced 4-wheel drive mapping and navigation technology with this cutting-edge robot car. Its sophisticated design enables efficient SLAM (Simultaneous Localization and Mapping) capabilities, making it ideal for autonomous robotics projects and intelligent navigation tasks.
The robot is engineered to work seamlessly alongside virtual machine environments, providing developers with a versatile platform to test and develop AI navigation algorithms. Its robust build supports precise control and real-time environmental mapping.
Equipped with powerful on-board sensors and processing units, this robot car excels at environment perception for accurate mapping and path planning. Its flexibility allows seamless integration in varied robotics projects including AI-driven exploration.
Its rugged chassis supports durable operation across diverse terrains, combined with advanced AI navigation capabilities powered by ROS2 frameworks. Ideal for education, prototyping, and AI research with real-world applications.
Integrated ROS2 AI SLAM technology facilitates real-time localization and mapping, turning the robot car into an autonomous vehicle capable of navigating complex environments with precision and efficiency.
Featuring the ESP32 AI Vision Module, this edition incorporates advanced AI visual recognition capabilities. It enables the robot to identify, interpret, and react to its surroundings, adding a new dimension to autonomous robotics applications.
Close-up view of the intelligent robot car highlighting its compact, durable construction and integrated sensors. This image showcases the intricate design and high-quality build optimized for advanced robotics development.
Another perspective showcasing the robot’s AI module and sensor array, emphasizing its state-of-the-art visual capabilities for SLAM and navigation. Ideal for researchers and makers looking to push autonomous tech boundaries.J’ai été surpris par la robustesse du châssis en aluminium, ça inspire confiance pour des projets longue durée. Le lidar ORBBEC offre un scan précis, idéal pour faire de la vraie cartographie avec ROS2. Le support technique de Yahboom est réactif et les cours très bien faits, même pour les débutants.
The robot kit’s neatly packed anodized aluminum chassis felt surprisingly premium as I lifted it from the box, promising both durability and style right from the start. Setting up the ESP32S3 board with microROS was straightforward, and I loved that it paired seamlessly with my PC’s virtual ROS2 environment—no pricey Pi or Jetson needed. The inclusion of the ORBBEC MS200 TOF LiDAR made real-time mapping in Rviz both precise and visually engaging, helping me clearly understand robot movement and navigation during my indoor mapping tests.
This microROS robot kit offers an affordable way to explore advanced ROS2 features without the need for pricey hardware like Jetson or Raspberry Pi. Its real-time data transmission and robust support for LiDAR mapping, navigation, and multi-robot coordination make it a versatile learning platform, while the included courses and tutorials help ease newcomers into complex topics. However, users with minimal hardware experience might face a learning curve when setting up the PC virtual machine environment. Overall, it's an excellent, cost-effective choice for DIY enthusiasts and students wanting to advance their robotics skills.
J'ai été bluffée par la facilité d’utilisation du kit microROS sur mon vieux PC. Le châssis en métal donne une vraie impression de robustesse et le LiDAR est super réactif pour la cartographie. J'apprécie aussi la batterie qui tient vraiment longtemps, ce qui est parfait pour tester plein de projets DIY à la maison.
From Hesitant Beginner to Confident Creator: My Journey with the
As someone eager to explore ROS2 but put off by the high price of Jetson or Raspberry Pi boards, I bought this microROS robot kit for its affordability. Before, learning ROS2 felt overwhelming and limited by my hardware; after setting up the kit and connecting it to my PC’s virtual machine, I was mapping rooms and planning paths within days. The visual Rviz feedback and hands-on tutorials not only clarified complex concepts but also inspired me to experiment with multi-robot projects, turning my curiosity into real technical skill and excitement.