- Suitable for simulating scenarios such as robot handling/inspection in factories
- Ultra-large high-definition canvas map of 4.1m × 3m
Yahboom AI large model scenario sandbox map (4.1m × 3m) is specifically designed for educational and competition-level robots, enabling practice in a variety of real-world tasks including warehouse logistics, factory transport, sorting, inspection, and obstacle navigation. It transforms any robotics lab, classroom, or competition venue into a fully functional AI simulation environment. The kit includes a complete set of props, such as color-coded EVA foam blocks (cubes, rectangular, and cylinders in 5 colors), 4-color sorting bins, visual positioning QR codes, multi-level shelving and sorting trays—providing everything needed out of the box to simulate industrial-grade robotic workflows.
Whether you are teaching a robotics course, preparing for national competitions, or prototyping autonomous navigation algorithms, this sandbox map offers the physical environment your robot needs to train and perform tasks.
1.Compatible with different types of experimental equipment: wheeled robots, ROS platforms, Raspberry Pi/Jetson AI robots, robotic arms, and so on.
2.Ultra-large high-definition canvas map of 4.1m × 3m, realistically replicating factory and logistics environments. Supports simultaneous operation of multiple robots, making it an ideal choice for robotics competitions, university laboratories, and any setting requiring a professional training field.
3.All items included: 40 cube EVA blocks, 25 rectangular EVA blocks, 25 cylindrical EVA blocks, 4-color sorting bins, 14 blue plastic pallets, 12 colorful pallets, 20 visual positioning QR codes, multi-layer wooden shelving, no need purchase additional props.
4.Supports a wide range of robot task scenarios, including factory material transport, waste sorting, parking lot navigation, visual recognition challenges, and patrol inspection, making it a versatile platform for teaching multiple AI and robotics concepts in a single environment.
