Published November 22, 2020 © GPL3+

Arduino Nano 33 BLE OV7670 Camera Shield

Embedded machine vision board, make your robotics ML enable.

IntermediateFull instructions provided5,811

Arduino Nano 33 BLE OV7670 Camera Shield

Things used in this project

Hardware components

OV7670 VGA Camera

Arduino Nano 33 BLE Sense

NXP PCA9685

Vishay TSOP38238

TDK Corporation PS1240

onsemi MC33269D-5.0G

WS2812B

15pin femaile pinheader

Slide Switch, SPDT-CO

Hand tools and fabrication machines

Soldering iron (generic)

Solder Wire, Lead Free

Reflo Air

Story

Arduino Nano 33 BLE processing capacity is moderately high for the low power consumption embedded system. Since it has many sensors on board, it seems to be very fun to run TinyML like software.

I thought it would be even more fun to connect vision, so I created a board with a low-cost camera OV7670 (around $3) connected.

In addition, the necessary power supply control, PWM controller IC for offloading servo processing, speakers, IR receiver, etc. were mounted.

Front View

The OV7670 connection is arranged so that the library (https://github.com/arduino-libraries/Arduino_OV767X) can be used. The camera is powered by 3.3V from the Arduino Nano 33 BLE.

Rear View

It is a little heavy to control the servo signal while executing the library for the camera and ML processing, so I connected PCA9685 PWM controller through I2C interface for servo control. This IC maintain servo control signal all the time.

Unlike the conventional nano, the Nano 33 can only supply 5V via USB power, so I have placed a voltage regulator that generates 5V from the battery. The battery is supposed to be rechargeable 9V, but any battery 6-20V can be connected.

It is also possible to supply 5V from an external system if you change power source select jumper. In that case, 5V will be supplied directly to the Nano 33 and servos.

In addition, NeoPixel (color RGB LED), piezo speaker, and IR receiver are added to enrich the expression or add the efficiency of program development.

Robot example

In the next report, I would like to introduce examples of small table robot and four-legged robot that use this board.

The printed circuit board is made by sending Gerber data to jlcpcb.com.

The article "Machine vision with low-cost camera modules" was very helpful for this design. Thank you very much.

Schematics

Code

OV767X

/*
  OV767X - Camera Capture Raw Bytes

  This sketch reads a frame from the OmniVision OV7670 camera
  and writes the bytes to the Serial port. Use the Procesing
  sketch in the extras folder to visualize the camera output.

  Circuit:
    - Arduino Nano 33 BLE board
    - OV7670 camera module:
      - 3.3 connected to 3.3
      - GND connected GND
      - SIOC connected to A5
      - SIOD connected to A4
      - VSYNC connected to 8
      - HREF connected to A1
      - PCLK connected to A0
      - XCLK connected to 9
      - D7 connected to 4
      - D6 connected to 6
      - D5 connected to 5
      - D4 connected to 3
      - D3 connected to 2
      - D2 connected to 0 / RX
      - D1 connected to 1 / TX
      - D0 connected to 10

  This example code is in the public domain.
*/

#include <Arduino_OV767X.h>

int bytesPerFrame;

byte data[320 * 240 * 2]; // QVGA: 320x240 X 2 bytes per pixel (RGB565)

void setup() {
  Serial.begin(9600);
  while (!Serial);

  if (!Camera.begin(QVGA, RGB565, 1)) {
    Serial.println("Failed to initialize camera!");
    while (1);
  }

  bytesPerFrame = Camera.width() * Camera.height() * Camera.bytesPerPixel();

  // Optionally, enable the test pattern for testing
  // Camera.testPattern();
}

void loop() {
  Camera.readFrame(data);

  Serial.write(data, bytesPerFrame);
}