navX 2016 Software Reset Displacement

[slibert]

Originally Posted by Jonathan L.

We did some more testing last night and I can't seem to get any reliable displacement readings. The performance seems to be far less than 1 meter/second per 15 seconds. Actually, I'm having a hard time figuring out which direction on a graph it thinks is forward. I did try running an initial gyro calibration, but it didn't seem to help. Any suggestions? I can upload the code if you like. The gyro seems to be working fine.

I also noticed using the zero velocity function seemed to reset everything until I rebooted.

Thanks.

If you have verified that the navX-MXP is firmly mounted to the robot (i.e., conceptually it should be part of the mass of the robot frame) as described on the RoboRIO installation page, then you've likely achieved the performance limit.

> 1 meter/second per 15 seconds

Note that units of displacement are meters, so units should be in meters rather than meters/second.

Since you mentioned zeroing the velocity, you may be attempting to integrate velocity to derive a displacement estimate. If you are indeed attempting to integrate the navX-MXP velocity estimates your results on average will be worse than if you use the displacement estimates calculated by the navX-MXP.

Here's a link to the paper describing in detail the algorithms used on the navX-MXP: http://www.nxp.com/files/sensors/doc...ote/AN3397.pdf

As you can see in the paper, this is a very complex algorithm, and is prone to a number of noise factors and other error-inducing conditions.

I highly recommend students interested in motion processing to become familiar with these algorithms, which is why they are present in the navX-MXP. As the technology advances in the upcoming years, it's expected that these same algorithms will continue to be used.

I'd be happy to review your code and look for issues - but please be aware my purpose in doing so would be for educational reasons. Since I understand your focus at the moment is positioning in autonomous, I want to reiterate this recommendation:

Bottom-line is that for autonomous our recommendation is to use some combination of navX-MXP's very accurate yaw angle with wheel encoders and/or sensors that measure distance to known pieces on the field (vision processing, ultrasonic, lidar). And as others have mentioned, due to the rough terrain encountered when crossing the defenses which can disturb encoders, using distance-measuring sensors and fusing that with navX-MXP yaw is likely the best approach.