Testing different methods to interface with a MPU-6050 or MPU-9250 via I2C or SPI. All methods feature the extraction of the raw sensor values as well as the implementation of a complementary filter for the fusion of the gyroscope and accelerometer to yield an angle(s) in 3 dimensional space.
Values retrieved below come from the MPU-6050 and MPU-9250 registry maps and product specifications documents located in the \Resources folder. Configure the gyroscope on 0x1B and the accelerometer on 0x1C as per data sheets with the following values (the MPU-6050 and MPU-9250 are interchangeable and all registries are the same):
| Accelerometer | Sensitivity | Gyroscope | Sensitivity | Hexadecimal | Binary |
|---|---|---|---|---|---|
| +/- 2g | 16384 | +/- 250 deg/s | 131 | 0x00 | 00000000 |
| +/- 4g | 8192 | +/- 500 deg/s | 65.5 | 0x08 | 00001000 |
| +/- 8g | 4096 | +/- 1000 deg/s | 32.8 | 0x10 | 00010000 |
| +/- 16g | 2048 | +/- 2000 deg/s | 16.4 | 0x18 | 00011000 |
The slave address is b110100X which is 7 bits long. The LSB bit of the 7 bit address is determined by the logic level on pin AD0. This allows two sensors to be connected to the same I2C bus. When used in this configuration, the address of one of the devices should be b1101000 (pin AD0 is logic low) and the address of the other should be b1101001 (pin AD0 is logic high). Communication will typically take place over the 0x68 register.
Ensure that the proper logic (3.3V vs 5V) is being used so you do not fry your sensor
Connect the sensor to the microcontroller as outlined below.
- VCC --> 5V or 3.3V based on specific breakout board and logic levels
- GND --> GND
- SDA and SCL pins located in table below:
| Board | SDA Pin | SCL Pin |
|---|---|---|
| Uno | A4 | A5 |
| Mega2560 | 20 | 21 |
| Leonardo | 2 | 3 |
| Due | 20 | 21 |
Upload the main.ino sketch and observe the values in the serial port or serial plotter. The calibrateGyro.ino sketch can be used to retrieve the offset values which can be directly placed into the main.ino sketch to eliminate the need for calibration every time the microcontroller is started up. Note that this is at the cost of performance as the sensors drift over time and between uses.
Connect an Arduino using the same wiring as outlined above. Run MATLAB\I2C\main.m and observe the values in the command line. MATLAB is extremely slow when using an Arduino/I2C connection.
A faster method is to read data through a serial connection. Using the same wiring connection, upload the sketch in Visualizer\arduinoSketch to the Arduino board. Adjust any desired parameters as outlined below in the MATLAB\serial\main.m file. Run and observe the values in the command line.
% Set up the class
gyro = 250; % 250, 500, 1000, 2000 [deg/s]
acc = 2; % 2, 4, 7, 16 [g]
tau = 0.98; % Time constant
port = '/dev/cu.usbmodem14101'; % Serial port name
Connect your IMU sensor to 5V or 3.3V based on specific breakout board and ground to ground. Refer to the pinout of your board using pinout.xyz and match SDA and SCL accordingly.
Setup as described here. First enter sudo raspi-config and enable SPI and I2C. Reboot the Pi.
Edit the modules file using sudo nano /etc/modules and ensure i2c-bcm2708 and i2c-dev are both in the file. Reboot again.
With the sensor correctly wired enter the following in the command line.
sudo apt-get install i2c-tools python-smbus
sudo i2cdetect -y 1
Which should yield the table below (possible to have the value 0x69) verifying a proper connection:
0 1 2 3 4 5 6 7 8 9 a b c d e f
00: -- -- -- -- -- -- -- -- -- -- -- -- --
10: -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
20: -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
30: -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
40: -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
50: -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --
60: -- -- -- -- -- -- -- -- 68 -- -- -- -- -- -- --
70: -- -- -- -- -- -- -- --
Once verified run python3 main.py to observe the values.
Follow the same setup guide as in the RPi (Python) section, however an MPU-9250 must be used.
The code is based on Kriswiner's C++ MPU-9250 library located here and Sebastian Madgwick's open source IMU and AHRS algorithms located here. To run the program navigate to the \9DOF directory and run python3 main.py.
Before running the program and sensor fusion algorithms the magnetometer must be calibrated. Uncomment the second line below and the program will walk you through all the required steps. Once values have been retrieved enter them in lines three and four below.
# Calibrate the mag or provide values that have been verified with the visualizer
# mpu.calibrateMagGuide()
bias = [282.893, 300.464, -91.72]
scale = [1.014, 1.054, 0.939]
mpu.setMagCalibration(bias, scale)
To verify the results of the calibration refer to the two articles located here and here. Place the values from the calibration into data.txt and magCalVisualizer.py and magCalSlider.py as described in the program guide during calibration. The magCalVisualizer.py and magCalSlider.py script will provide all the required plots to aid in verifying the results as well as interactive sliders to optimize values.
Note that the magnetometer can either be read as a slave or in direct mode. Both methods exist with slave being the default mode.
Connect an IMU device as outlined in the Arduino section. Upload the sketch located in Visualizer/arduinoSketch. This sketch simply transmits the raw byte data from the sensor over a serial connection.
Next, install the required packages by performing these steps:
cd MPU-6050-9250-I2C-CompFilter/render
npm install
Edit the file main.js file located in Visualizer/render to set the correct serial port and any other parameters of interest.
// Customize these values
const serialPortName = 'COM4';
const serialBaud = 9600;
var tau = 0.98;
var gyroScaleFactor = 65.5;
var accScaleFactor = 8192.0;
var calibrationPts = 250;
Once all the values are customized start the serial port server by navigating to Visualizer/render and entering:
node main.js
In your default browser enter localhost:3000 and the visualizer should be running.
Ensure to hold the IMU device still until an object appears on the screen. This is the program performing a calibration for gyroscope offset.
See full instructions and example code at https://github.com/MarkSherstan/STM32-MPU6050-MPU9250-I2C-SPI. Support for:
- I2C using CPP
- I2C using C
- SPI using CPP (MPU-9250 only)
- SPI using C (MPU-9250 only)
A generic C++ library was written that can be used on a variety of hardware. Refer to the Arduino or Raspberry Pi example in the CPP_library directory to get an idea of how to use the library.
For the Arduino example ensure to add the library to your Arduino IDE or put the mpuXX50.h and mpuXX50.cpp in the same folder as your *.ino.
For the Raspberry Pi you may need to run the following commands before using the Makefile.
sudo apt-get install libi2c-dev
sudo apt-get install i2c-tools
sudo apt-get update
sudo i2cdetect -y 0
//or
sudo i2cdetect -y 1
Upon setting up the class with the I2C address of the sensor and defining the read and write functions the library has the capability to.
- Perform WHO_AM_I sensor self check
- Set the resolution of the accelerometer and gyroscope
- Perform, set, and return gyroscope calibration values
- Return raw sensor values, calibrated sensor values, and complementary fused values yielding sensor attitude - roll, pitch, and yaw (yaw will drift over time)
- Add quaternion angle representation
- Kalman filter (custom lib)
- C Library
- General clean up
- Use updated hardware