Machine Vision Bundle
A rapid solution for embedded machine learning (ML) combining vision, audio and connectivity. Open the lenses to a new territory of lean and efficient image processing applications for your Arduino projects.
Overview
The Arduino Portenta Vision Shield is a production-ready expansion for the powerful Arduino Portenta H7. It adds a low-power camera, two microphones, and connectivity; everything you need for the rapid development of edge ML applications.
The Portenta H7 simultaneously runs high-level code along with real-time tasks. The
H7's main processor is a dual-core STM32H747 including a Cortex® M7 running at 480MHz and a Cortex® M4 running at 240MHz. The two cores communicate via a Remote Procedure Call mechanism that allows seamless calling of functions on the other processor.
Both processors share all the in-chip peripherals and can run:
- Arduino sketches on top of the Arm® Mbed™ OS
- Native Mbed™ applications
MicroPython / JavaScript (via an interpreter)
TensorFlow™ Lite
Moreover, the onboard wireless module allows the simultaneous management of WiFi and Bluetooth® connectivity on the Portenta H7.
The Portenta Vision Shield brings industry-rated vision and audio capabilities to your Portenta H7. This hardware add-on lets you run embedded computer vision applications, connect wirelessly or via Ethernet to the Arduino Cloud or your own infrastructure, and activate your system using sound detection.
The Vision shield comes with a 324x324 pixels camera module that contains an ultra low power image sensor designed for always-on vision devices and applications. The high sensitivity image sensors can capture gestures, ambient light, proximity sensing and object identification.
There’s a plethora of applications you can deploy with Portenta H7 and Portenta Vision Shield. The demonstration below shows how to implement an accurate digits recognition system using Edge Impulse. Digits recognition using computer vision is desirable in many application and market areas, such as grocery retail, manufacturing, utility metering, and administration.
Learn how to implement accurate digit recognition using Edge Impulse.
Check out the documentation to easily implement Portenta H7 and Portenta Vision Shield in your projects.
Arduino IoT Cloud Compatible
Use your MKR board on Arduino's IoT Cloud, a simple and fast way to ensure secure communication for all of your connected Things.
Need Help?
Check the Arduino Forum for questions about the Arduino Language, or how to make your own projects with Arduino. If you need any help with your board, please get in touch with the official Arduino User Support as explained on our Contact Us page.
Warranty
You can find your board warranty information here.
Tech specs
The Machine Vision Bundle includes:
Resources for Safety and Products
Manufacturer Information
The production information includes the address and related details of the product manufacturer.
Arduino S.r.l.
Via Andrea Appiani, 25
Monza, MB, IT, 20900
https://www.arduino.cc/
Responsible Person in the EU
An EU-based economic operator who ensures the product's compliance with the required regulations.
Arduino S.r.l.
Via Andrea Appiani, 25
Monza, MB, IT, 20900
Phone: +39 0113157477
Email: support@arduino.cc
Get Inspired
As robotics advance, the future could certainly involve humans and automated elements working together as a team. The question then becomes, how do you design such an interaction? A team of researchers from Purdue University attempt to provide a solution with their GhostAR system. The setup records human movements for playback later in augmented reality, while a robotic partner is programmed to work around a “ghost” avatar. This enables a user to plan out how to collaborate with the robot and work out kinks before actually performing a task. GhostAR's hardware includes an Oculus Rift headset and IR LED tracking, along with actual robots used in development. Simulation hardware consists of a six-axis Tinkerkit Braccio robot, as well as an Arduino-controlled omni-wheel base that can mount either a robot an arm or a camera as needed. More information on the project can be found in the team's research paper. With GhostX, whatever plan a user makes with the ghost form of the robot while wearing an augmented reality head mount is communicated to the real robot through a cloud connection – allowing both the user and robot to know what the other is doing as they perform a task.The system also allows the user plan a task directly in time and space and without any programming knowledge.First, the user acts out the human part of the task to be completed with a robot. The system then captures the human’s behavior and displays it to the user as an avatar ghost, representing the user’s presence in time and space.Using the human ghost as a time-space reference, the user programs the robot via its own ghost to match up with the human’s role. The user and robot then perform the task as their ghosts did.
