In this post we show how to create a Digital Spirit Level using a Raspberry Pi and python.
The code moves that bubbles on the display in relation to the angle read from the IMU.
Parts used in this project;
Any IMU or TFT can be used, however the code would need to be updated to accommodate the different devices. It is best to use a 480×320 TFT as the images are scaled to fit this resolution.
This guide assumes that some basic understanding of an IMU(Accelerometer and Gyroscope) is already known. And you have one already working with your Raspberry Pi.
If you don’t, we do have some guides which covers this.
We have used our existing python code to read the values from the IMU, however we have removed the code related to the magnetometer as it isn’t needed for this project.
Git repository here
The code can be pulled down to your Raspberry Pi with;
pi@raspberrypi ~ $ git clone http://github.com/mwilliams03/BerryIMU.git
Placement of IMU
The IMU can be attached anywhere, however it is best to place it in the same orientation as shown below. If you do change the orientation, you will need to update the code accordingly.
We have updated to the python code in our git repo.
It now includes;
- The elusive Kalman filter.
- Math needed when the IMU is upside down
- Automatically calculate loop period.
- A lot more comments.
What is a Kalman filter? In a nutshell;
A Kalman filter is, it is an algorithm which uses a series of measurements observed over time, in this context an accelerometer and a gyroscope. These measurements will contain noise that will contribute to the error of the measurement. The Kalman filter will then try to estimate the state of the system, based on the current and previous states, that tend to be more precise that than the measurements alone.
A Kalman filter is more precise than a Complementary filter. This can be seen in the image below, which is the output of a complementary filter (CFangleX) and a Kalman filter (kalmanX) from the X axis plotted in a graph.
The red line (KalmanX) is better at filtering out noisep;
The code can be found here in our Git repository here
And can be pulled down to your Raspberry Pi with;
pi@raspberrypi ~ $ git clone https://github.com/mwilliams03/BerryIMU.git
A summary of the code;
def kalmanFilterY ( accAngle, gyroRate, DT):
KFangleY = KFangleY + DT * (gyroRate - y_bias)
YP_00 = YP_00 + ( - DT * (YP_10 + YP_01) + Q_angle * DT )
YP_01 = YP_01 + ( - DT * YP_11 )
YP_10 = YP_10 + ( - DT * YP_11 )
YP_11 = YP_11 + ( + Q_gyro * DT )
y = accAngle - KFangleY
S = YP_00 + R_angle
K_0 = YP_00 / S
K_1 = YP_10 / S
KFangleY = KFangleY + ( K_0 * y )
y_bias = y_bias + ( K_1 * y )
YP_00 = YP_00 - ( K_0 * YP_00 )
YP_01 = YP_01 - ( K_0 * YP_01 )
YP_10 = YP_10 - ( K_1 * YP_00 )
YP_11 = YP_11 - ( K_1 * YP_01 )
Luca has written up a great tutorial on the differences between delay() and millis() on the Arduino, which i think is worthwhile to share. He also presents it in a very easy to understand format.
Source: lucadentella.it – Arduino, delay() vs millis()
To create an awesome audio visualizer, using a spectrum analyzer( C.A.V.A: Console-based Audio Visualizer for ALSA ), all you need is a Raspberry Pi 3 and a RGB LED cube – VoxCube!
CAVA was created by Karl Stavestrand and it is a great tool to create an audio visualizer in the console.
In this tutorial I am going to show you how to program an AVR(ATmega328) and an Arduino UNO using the GPIO on the Raspberry Pi.
Adding an Arduino or an AVR to your projects will give you much greater flexibility.
Hook up the Raspberry Pi to the Arduino UNO or AVR.
The image below shows how to connect a Raspberry Pi 2 and an Arduino UNO. click the image to make it larger
The above LED cube [VoxCube] is being controlled via a Raspberry Pi, using python and the official Raspberry Pi display.
Buttons were setup using the Kivy. Kivy is a Python library which makes creating buttons and events with a touchscreen very easy.
Here is a very good guide on how to get Kivy setup on a Raspberry Pi.
We have been busy over the last 6 months creating something special!
We have always liked the idea of LED cubes, however there was no easy way to drive these LED cubes with a Raspberry Pi…. until now.
VoxCube is an 8x8x8 RGB LED Cube which has been specifically designed for the Raspberry Pi, however it is also compatible with other microcontrollers. E.g. Arduino
Cubes can also be chained together, the image below is four VoxCubes being controller via a Raspberry Pi.
Head over to the Kickstarter page for more details.