I am building a balancing robot using the Lego Mindstorm's NXT system. I am using two sensors from HiTechnic, the first being an Accelerometer and the second being a Gyroscope. I've successfully filtered out noise from both sensors and derived angles for both in a range between -90 and 90 degrees, with 0 degrees being perfectly balanced.

My next challenge is to combine both of the sensor values to correct for the Gyroscope's drift over time. Below is an example graph I created from actual data to demonstrate the drift from the gyroscope:

![enter image description here](https://i.stack.imgur.com/AHx4r.png)

The most commonly used approach I've seen to make combining these sensors rock solid is by using a Kalman filter. However, I'm not an expert in calculus and I really don't understand mathematical symbols, I do understand math in source code though.

I'm using RobotC (which is like any other C derivative) and would really appreciate if someone can give me examples of how to accomplish this in C.

Thank you for your help!

**SOLUTION RESULTS:**

Alright, kersny solved my problem by introducing me to complementary filters. This is a graph illustrating my results:

*Result #1*

![enter image description here](https://i.stack.imgur.com/MqRid.png)

*Result #2*

![enter image description here](https://i.stack.imgur.com/mePBt.png)

As you can see, the filter corrects for gyroscopic drift and combines both signals into a single smooth signal.

**Edit:** Since I was fixing the broken images anyways, I thought it would be fun to show the rig I used to generate this data:

![enter image description here](https://i.stack.imgur.com/hWbBh.jpg)