Category Archives: MicroPython

Remove Long Term Steady State Errors from MPU6050 Tilt Measurements

In this video lesson I show you how to remove long term steady state error from the tilt values calculated from the MPU6050 IMU. We are using the following schematic for our prototype.

Schematic for Creating a Tilt Meter

For your convenience, this is the code we developed in the video.

 

Improving Accuracy of MPU6050 Data Using a Complimentary Filter

In this video lesson we show how to create a complimentary filter such we get pitch and roll data from the MPU6050 which is quick and responsive, accurate, and low noise. We are using the following schematic:

Schematic for Creating a Tilt Meter

This is the code we developed in the video.

 

Measuring Roll, Pitch, and Yaw Using 3-Axis Gyro on the MPU6050

In this video lesson we describe how to measure roll, pitch, and yaw using the MPU6050. We describe the issues associated with drift in these gyros and will propose a path forward in dealing with the drift issue.

We are using the following circuit for this project:

Schematic for Creating a Tilt Meter

And this is the code we develop in today’s lesson.

 

Two Axis Tilt Meter Displaying Pitch and Roll Using an MPU6050 on the Raspberry Pi Pico W

In this video lesson, we demonstrate how to create a two-axis tilt meter. The device displays both the pitch and roll on an OLED. In addition to this quantitative display of tilt and roll, it also shows a carpenter’s level type visual, where a circle, or bubble moves to indicate tilt. When the circle is centered on the crosshairs, the device is flat in both axis.

For your convenience, this is the schematic we are using:

Schematic for Creating a Tilt Meter

And we also include the code we developed in this lesson.

 

Convert HSV to RGB in Micropython


In this video lesson we showed how to convert an angle on the HSV color wheel into an RGB value that can be applied to an RGB LED. In effect, we can find a color we like on the HSV color wheel, and turn the LED in our project that color. The video above shows the framework we are using, and then derives the equations, and then develops the code. For your convenience, the code for the conversion is shown below. To make this a library, we save it as h2RGB.py on our Raspberry Pi Pico W. You can save it either in the same folder your main programs are in, or in the lib folder. To use the library, then simply import the file (h2RGB) and call the method h2RGB.getRGB(degrees), where degrees is the point on the HSV color wheel you want to convert. All of this is explained in detail in the above video.