Arduino® UNO Q Integration YAHBOOM DOGZILLA S1-2 KIT

5000mAh Charger power bank

Arduino® UNO™ Q 4GB

Modulino™ LED Matrix

Arduino App Lab

Modulino™ Buzzer

Arduino USB-C Hub (8 in 1)

Yahboom Dogzilla S1 Quadruple 

Modulino™ Movement

<html><body>Robodog V2.0 transforms the Yahboom DOGZILLA S2 into an AI-enabled quadruped powered by the Arduino® UNO Q. Instead of using the original Raspberry Pi controller supplied with the robot, the Arduino UNO Q becomes the new computing platform while retaining the factory DOGZILLA motion controller. This architecture combines a Linux application processor with an integrated MCU, allowing high-level AI workloads and deterministic real-time motor control to run on a single board. The system was developed entirely using Arduino® App Lab, RouterBridge, and Modulino peripherals, creating a modular robotics platform suitable for education, research, rapid prototyping, and embedded AI demonstrations. Arduino® Uno Q - The Rockstar :) <figure><img src="https://projects.arduinocontent.cc/6db9fdfe-cb0f-40a2-b991-0aace65bf242.jpg"/><figcaption>UNO Q</figcaption></figure> Arduino® UNO Q integrates the Qualcomm® QRB2210 Microprocessor (MPU), running a full Debian-based Linux environment, with the STMicroelectronics® STM32U585 Microcontroller (MCU) built on Arm® Cortex®-M33 architecture, all within the compact UNO form factor. This dual-architecture platform combines high-performance computing with deterministic real-time control, delivering the power and versatility needed for modern AI at the edge applications. <figure><iframe src="https://youtu.be/p2OpvfR2xfI?si=0qx1jFC8L9mJffTF"></iframe></figure> Unlock hybrid development with Arduino® App Lab, seamlessly uniting Python applications, Arduino sketches, and AI models in a single workflow. From AI-powered vision and sound solutions that react intelligently to their environment to sophisticated smart home systems, UNO Q with Arduino App Lab delivers next-generation embedded innovation to makers, educators, and professionals alike. At the same time, developers enjoy true freedom of choice: program the MCU subsystem with the Arduino IDE, or integrate Arduino CLI into existing workflows with popular editors like VS Code. Project Objectives <ol><li>Learn how to integrate with Arduino® UNO Q </li><li>Preserve the original DOGZILLA servo controller </li><li>Keep the original UART protocol </li><li>Build a completely offline AI robot </li><li>Use Arduino® App Lab as the primary development environment </li><li>Create a modern WebUI </li><li>Add onboard sensors through Modulinos </li><li>Support Edge Impulse AI models </li><li>Provide an extensible robotics platform </li></ol> Link to the YouTube short teaser : <a href="https://www.youtube.com/shorts/KNFR_PgUWUQ">https://www.youtube.com/shorts/KNFR_PgUWUQ </a>WIRING DIAGRAM <figure><img src="https://projects.arduinocontent.cc/44701db8-85cb-4387-86a9-d4a239b63925.png"/><figcaption>Arduino® Uno Q integration with YAHBOOM Quadruplet</figcaption></figure>System Architecture &amp; Software Overview Video created by Tyler Wojciechowicz <figure><iframe src="https://youtu.be/KKpNTTjLSfE"></iframe></figure> For the Robodog V2.0 software integration, we built a split architecture using the Arduino UNO Q as both the high-level Linux computer and the low-level MCU controller. The Linux side runs the App Lab application, WebUI, USB camera stream, Edge Impulse Object Detection brick, gamepad handling, and automation logic. The MCU side runs the DOGZILLA control firmware, preserving the original Yahboom DOGZILLA S2 motion controller and communicating with it over the same UART protocol. On the MCU firmware side, we created a RouterBridge-based sketch that exposes DOGZILLA movement commands to the Linux application. Commands like forward, backward, left, right, stop, battery query, and preset actions are sent from Python to the MCU using Bridge.call(). The MCU then converts those requests into DOGZILLA UART packets and sends them through Serial1 to the original DOGZILLA controller. This keeps the real-time robot motion layer simple and stable while allowing the Linux side to focus on AI and UI features. We also integrated multiple Arduino Modulino sensors on the Qwiic/I²C bus using the arduino_modulino library. The Modulino Matrix provides robot facial expressions, startup animation, directional arrows, battery icons, action signs, and feedback for AI events. The Modulino Movement provides accelerometer and vibration data that is exposed to the WebUI. The Modulino Buzzer provides signal indication on movements to keep the user alerted. On the Linux/App Lab side, we built a Python application using the App Lab WebUI brick and Object Detection brick. The WebUI provides manual robot controls, preset action buttons, live camera preview, vibration and distance status, gamepad status, gesture detection controls, and system state. The camera stream runs in a background thread using OpenCV, while the WebUI refreshes frames in the browser so the user can see real-time video from the USB camera. For AI behavior, a Qualcomm AI HUB or Edge Impulse model is selected inside the Object Detection brick. The Python app continuously analyzes camera frames when gesture detection is armed. Overall, the software stack turns the Yahboom DOGZILLA S2 into a modular AI robot controlled by the Arduino UNO Q. The original DOGZILLA motion controller remains responsible for locomotion, while UNO Q adds a modern web interface, local AI inference, camera streaming, gesture recognition, gamepad support, sensor-based behaviors, and visual feedback through the Modulino Matrix. DOGZILLA S2 UNBOXING AND MOUNTING EXPERIENCE *Screws and tools are included in the Yahboom kit. Wires from the connector to the Uno Q are not included and must be bought separately. <figure><img src="https://projects.arduinocontent.cc/0f1fdc26-c6ce-44e8-86f9-698b90c7ca7c.jpg"/><figcaption>DOGZILLA s2</figcaption></figure> <figure><img src="https://projects.arduinocontent.cc/bf4a7bc7-36e0-42cd-8b37-69d686e41cdd.jpg"/><figcaption>Arduino Uno Q mounting example</figcaption></figure> <figure><img src="https://projects.arduinocontent.cc/7e522992-cdfe-4c70-902a-b0903e85791b.jpg"/><figcaption>Raspberry Pi connector with TX/RX AND GND connector to the UNO Q</figcaption></figure> <figure><img src="https://projects.arduinocontent.cc/fb909606-7444-41de-9fe8-52d5e8975cdf.png"/><figcaption>UNO Q wiring</figcaption></figure> <figure><img src="https://projects.arduinocontent.cc/7854eaf0-6d75-4e56-8265-46ffca073f3e.jpg"/><figcaption>Full assembly with camera case completed. (screws are included with the Yahboom kit)</figcaption></figure> ROBODOG ACCESS POINT SETUP You can create the UNO Q offline WiFi access point so a phone can connect directly to the robot and use the WebUI without internet. 1.- Open a terminal inside the UNO Q using App Lab, and run this command: <pre>sudo nmcli device wifi hotspot \ </pre><pre>	 ifname wlan0 \ </pre><pre>	 con-name DOGZILLA-UNOQ \ </pre><pre>	 ssid DOGZILLA-UNOQ \ </pre><pre>	 password dogzilla123 </pre>2.- Verify the hotspot was created: <pre>nmcli connection show </pre>You should see: <pre>DOGZILLA-UNOQ </pre>3.- Configure Automatic Reconnection After Reboot Enable automatic startup of the hotspot: <pre>sudo nmcli connection modify DOGZILLA-UNOQ \ </pre><pre>	 connection.autoconnect yes </pre>Increase its priority so it is preferred during boot: <pre>sudo nmcli connection modify DOGZILLA-UNOQ \ </pre><pre>	 connection.autoconnect-priority 100 </pre>(Optional) Bind the profile to the wireless interface: <pre>sudo nmcli connection modify DOGZILLA-UNOQ \ </pre><pre>	 connection.interface-name wlan0 </pre>4.- Verify the Configuration Confirm that auto-connect is enabled: <pre>nmcli connection show DOGZILLA-UNOQ </pre>Look for: <pre>connection.autoconnect: yes </pre><pre>connection.autoconnect-priority: 100 </pre>Verify that the wireless interface is active: <pre>nmcli device status </pre>Expected output: <pre>DEVICE TYPE STATE CONNECTION </pre><pre>wlan0 wifi connected DOGZILLA-UNOQ </pre>Confirm the hotspot IP address: <pre>ip addr show wlan0 </pre>Expected address: <pre>10.42.0.1/24 </pre>After you have set the access point up, you should be able to access the interface URL using the expected address 10.42.0.1/24 <figure><img src="https://projects.arduinocontent.cc/bd44b3bd-310d-48b9-8d83-d56a9256d307.jpg"/><figcaption>WIFI URL interface</figcaption></figure> ROBODOG APP LAB </body></html>

Robodog Pro v8.4.8

Arduino_UNOQ_DOGZILLA_Integration_Guide_ProjectHub_Engineering

Arduino® UNO Q Integration YAHBOOM DOGZILLA S1-2 KIT

Robodog Arduino solution transforms the Yahboom DOGZILLA S2 into an AI-enabled quadruped powered by the Arduino® UNO Q