VENTUNO Q Integration with JetArm

Arduino USB-C Power Supply (65W)

Adapter USB C to DC power Cable

JetArm

Ubuntu Linux

Arduino USB 2.0 CABLE TYPE A/B 1M

Mini Keyboard and Mouse

Arduino®️ VENTUNO™ Q

USB Extender hub

Hiwonder JetArm

Arduino App Lab

<html><body>This project integrates the Hiwonder JetArm robotic arm with the Arduino VENTUNO Q to create an Edge AI robotics demonstration combining computer vision, voice recognition, ROS 2 control, and a web-based user interface. <figure><img src="https://projects.arduinocontent.cc/ae5ec7f1-d1d4-491b-a6c7-ade3e08b3374.png"/><figcaption>Arduino Ventuno Q ( IQ8 Dragonwing with 40 Dense TOPS)</figcaption></figure> VENTUNO Q operates as the main AI and application-processing platform. Arduino App Lab performs the AI workloads, while ROS 2 provides the communication and motion-control layer for the JetArm servos. The current demonstration uses two AI capabilities: <ol><li>Face/Person Detection: Detects and tracks a person using the camera. The detected target position is converted into pan and tilt corrections so the JetArm can continuously follow the user. </li></ol><ol><li>Automatic Speech Recognition (ASR): Allows the robot to respond to voice commands such as Follow me, Stop tracking, Center robot, and Emergency stop. </li></ol>The application demonstrates a complete perception → decision → action workflow on an embedded Edge AI platform. <figure><img src="https://projects.arduinocontent.cc/e7adcc3c-420a-4fca-91e2-17e8f9db361c.png"/><figcaption>Full Project Example</figcaption></figure> Objectives The objective of this project was to showcase the capabilities of Arduino VENTUNO Q as a robotics and Edge AI platform by integrating it with the Hiwonder JetArm robotic arm. The goal was not simply to move the robot, but to demonstrate how VENTUNO Q can act as the central computing platform for a complete robotics application that combines: <ol><li>ROS 2 robotic control </li><li>AI-based face/person detection </li><li>Automatic Speech Recognition (ASR) </li><li>Real-time interaction with a robotic arm </li><li>Arduino App Lab for application development and integration </li></ol>The demonstration was designed to show that VENTUNO Q can manage multiple workloads at the same time: running AI inference, processing camera and microphone inputs, executing application logic, communicating with ROS 2 nodes, and generating physical movement through the JetArm. Wiring Diagram <figure><img src="https://projects.arduinocontent.cc/be6a1bea-ce30-4f8a-a17b-fbf605eeeb04.jpg"/><figcaption>HIWONDER JETARM OUT OF BOX</figcaption></figure> <figure><img src="https://projects.arduinocontent.cc/e501aa92-f7eb-4484-a18f-9c08d4fa4549.jpg"/><figcaption>FULL WIRING INTEGRATED</figcaption></figure>YouTube video Link : <a href="https://youtube.com/shorts/qbho7HyzSb4?si=kyJz9SqUKUQUzZ4o">https://youtube.com/shorts/qbho7HyzSb4?si=kyJz9SqUKUQUzZ4o</a>Recommendations: <figure><img src="https://projects.arduinocontent.cc/64ad67b8-8721-4146-959f-1c801b775761.png"/><figcaption></figcaption></figure> </body></html>

Arduino AI RoboArm Studio V1.2

JetArm with Ventuno Q

VentunoQ with JetArm application guide

VENTUNO Q Integration with JetArm

The JetArm Face-tracking and Voice control solution developed on Ventuno Q running Ubuntu features camera-based AI detection and Automatic Speech Recognition (ASR) control via ROS 2 and interfaced via Arduino App Lab