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MU Vision Recognition Sensor

SKU: SEN0314

The MU Vision Sensor integrates a built-in deep-learning engine and a wide-angle 30W lens, enabling onboard image recognition without cloud processing. It supports multiple vision algorithms—including color detection, object localization, face/human detection, ball tracking, and card recognition—allowing robots to perceive their environment and respond autonomously. The module provides UART, I²C, and WiFi communication through a Gravity interface, and supports direct configuration and firmware updates via its onboard USB serial port. Compact in size and compatible with Arduino, micro:bit, and Mind+ graphical programming, the MU Vision Sensor is easy to integrate into educational, robotic, and embedded applications.

Front of a small black vision sensor module with labeled pins and LED indicator-DFRobot product sku:SEN0314 image.

Downloadable Resources

  • Docs
  • Tech Specs

    • 1. Getting Started

    This section shows the basic steps to set up and operate the MU Vision Sensor.

    2. Example Code for Arduino-UART Mode

    The project uses the MU Vision Sensor in UART mode to detect various objects (e.g., traffic cards) and output their center coordinates, size, and label.

    3. Example Code for Arduino-I2C Ball Detection

    This project uses the MU Vision Sensor in I2C mode to detect ping-pong balls or tennis balls and outputs their center coordinates, size, and label.

    4. Example Code for Arduino-I2C Color Recognition

    This project uses the MU Vision Sensor in I2C mode to recognize colors and output the RGB values and color label. Users learn color recognition setup.

    5. Example Code for Arduino-I2C Human Detection

    This project uses the MU Vision Sensor in I2C mode to detect the upper body of a human and output the center coordinate and size of the bounding box. Users learn human detection setup.

    6. Example Code for Arduino-I2C Card Detection

    This project uses the MU Vision Sensor in I2C mode to detect customized cards (shape, traffic, number) and output their center coordinate, size, and label. Users learn card detection setup.

    7. Example Code for micro:bit-Mind+ Graphical Programming

    This project uses Mind+ graphical programming with the micro:bit to program the MU Vision Sensor for number card detection. The result is displayed on the micro:bit. Users learn Mind+ setup and graphical programming.

    Reference

    Specification

    Parameter Details
    Processor dual-core, 240MHz
    Camera Omnivision ov7725
    Camera Resolution 640x480
    Field of View 90° (Diagonal line)
    LED lights 2
    Dimension 3.23.21.2cm/1.261.260.47”
    Data Output UART/IIC
    Power Supply 5V
    Detected Objects - people silhouette (above the waist)
    - Ball (Ping-pong ball or tennis ball)
    - 20 Customized Cards
    - Color (Within the detection range, output the color of the designated position or output the position of the designated color)
    Functions In Development - WiFi Image Transmission (module as AP)
    - Motion Routine Detection (detection of hand movement from top to bottom, left to right, etc,. non-gesture sensing)
    - Face recognition
    - QR code recognition

    Pinout

    SEN0314 MU Vision Sensor Pinout
    label Description
    G Ground
    V Power Input(3.3V or 5V)
    TX Serial Port transmitter
    RX Serial port receiver
    SCL Control line
    SDA Data line

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