Physical AI needs a board that can think and act at the same time. This project pairs a Qualcomm Dragonwing IQ8 processor with an STM32H5 in a dual-brain architecture. The first runs AI models with 40 TOPS, while the second controls motors and peripherals in real time. The result is a complete platform for robotics and automation.

The board carries 16 GB of LPDDR5 RAM and 64 GB of eMMC storage. Connectivity includes tri-band Wi-Fi 6, Bluetooth 5.3, 2.5 Gb Ethernet, and CAN-FD. The board with integrated display from the Arduino UNO Q family offers a similar starting point for anyone approaching this world. The project board is open source and free of proprietary lock-ins.

How the dual-brain architecture works

The Qualcomm Dragonwing IQ8 processor handles the artificial intelligence. The STM32H5, on the other hand, guarantees deterministic control over motors, CAN bus, and other peripherals. The two processors communicate efficiently, so the AI can make decisions and the hardware executes without unpredictable latencies.

The preinstalled operating system is Ubuntu with an Ubuntu Pro license. The Arduino core runs on Zephyr RTOS, which offers guaranteed response times. In addition, the environment supports VS Code, PyCharm, Jupyter, and Docker for development.

AI models optimized for the NPU run through Arduino App Lab. The platform supports importing GGUF models from Hugging Face and training with Edge Impulse Studio. There are over 100 ready-to-use examples.

• 40 TOPS of AI power
• 16 GB LPDDR5 RAM
• 64 GB eMMC
• Tri-band Wi-Fi 6 (2.4/5/6 GHz)
• Bluetooth 5.3
• 2.5 Gb Ethernet
• CAN-FD

Why a board for Physical AI is needed

Modern robotics requires perception, decision, and action in a single device. This board unifies everything in an open format. Makers can prototype with Arduino UNO shields and Raspberry Pi HATs. Moreover, ROS 2 support and the CAN-FD, I2C/I3C, SPI, PWM, and UART interfaces make it suitable for professional projects.

Compatibility with existing shields lets you reuse sensors and actuators you already own. For example, those with the more powerful processor board from the Raspberry Pi family can compare performance. In addition, the Works with Arduino program allows scaling prototypes to production level with certified SOMs from SECO and Toradex.

An open ecosystem for physical AI

The board uses Ubuntu Pro as its main operating system. Zephyr RTOS handles real-time hardware control. This mix ensures flexibility for development and robustness for execution.

Arduino App Lab is the access point for AI models. It supports importing from Hugging Face and training with Edge Impulse. There are also over 100 ready-made examples to get started right away.

The board is powered by a 65W USB-C power supply. It is designed for those who want to move from prototyping to production without changing platforms. Finally, support for Arduino shields and Raspberry Pi HATs makes it versatile.

For those starting out with embedded AI, the board with the STM32 microcontroller offers a simpler alternative. However, this board represents the next step for advanced robotics projects. Physical AI thus becomes accessible to makers, educators, and professionals.

Source: https://www.qualcomm.com/internet-of-things/products/iq8-series

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