Anti-tipping algorithm

[Jared Russell]

Originally Posted by NotInControl

Cool idea. For anyone that wants to try this. You don't need to buy any additional sensors, the RoboRio has a built in accelerometer, and you can use that alone to sense pitch and roll angles, depending on how the RoboRio is mounted with relation to your Robot.

Here is some code to get you started:

public static double getAccPitch() {
	
	double Y = Robot.accel.getY();
	double Z = Robot.accel.getZ();
	

	return Math.atan2(Y,Z) *180 /Math.PI;
}

public static double getAccRoll()
{
	
	double X = Robot.accel.getX();
	double Y = Robot.accel.getY();
	double Z = Robot.accel.getZ();
	
return Math.atan2(-X, Math.sqrt(Y*Y + Z*Z)) * 180/Math.PI;

}

You will need to switch the methods if you mount your RoboRio vertically.

To access the built-in accelerometer in the RoboRio simply do this:

public static BuiltInAccelerometer accel;
accel = new BuiltInAccelerometer();

The above code assumes you instantiated the accelerometer in Robot.java, but you can do it anywhere you like.

Hope this helps,

Regards,
Kevin

This approach will make it appear that your robot is pitching or rolling any time you have acceleration due to any force other than gravity (such as the reactive force exerted by the carpet against the tractive force of your wheels).

[Gdeaver]

As Jared mentioned, a pure accelerometer solution is going to have noise and accelerations in it. Filtering can clean it up some what to give an estimation of gravity but the robot acceleration is still there. The advantage to the Navx MXP is that the chip handles the fusion of 3 a axis accelerometer and a 3 axis gyro.
It also can fuse a 3 axis magnetometer also but we do not use the mag. Pitch and roll are very solid and excellent for this use. Yaw is another subject. In it's current form the Navx MXP does need to be horizontal.

[NotInControl]

Originally Posted by Jared Russell

This approach will make it appear that your robot is pitching or rolling any time you have acceleration due to any force other than gravity (such as the reactive force exerted by the carpet against the tractive force of your wheels).

That is very true... the induced acceleration due to robot motion will appear as high frequency noise on each signal. The great thing about that, is that it is easy to determine which acceleration is legitimate, and which acceleration is induced due to robot motion. Simple Low pass filters, will allow for more stable readings... but will increase delay. There is a happy medium to allow for reliable tilt measurements.

A simple Euler linear filter can be used if one desires. It is a autoregressive infinite impulse response moving average.

accelX = (accelX * alpha) + (Robot.accel.getX() * (1.0 - alpha));

Where alpha is a value from 0 to 1. as you increase alpha from 0 towards 1, the filtering gets more aggressive, and the delay increases. If alpha is 0, its easy to see that there is no filtering at all.

This is the most basic filter you can implement in my book, and it does a pretty good job. There are more robust filters if you ever wanted to experiment with them. Two popular filters to try to smooth acceleration data out would be a median filter, or a Butterworth filter. They are popular because they are relatively easy to implement in code.

If you have the means to use a Gyro to measure the axis of rotation you care about, that is the sensor I would recommend for this application... if you don't, or want to experiment otherwise, it shouldn't take too much effort to use an accelerometer to have a similar implementation.