How to reduce latency under mean filter for high noise?
Although this is an old entry and probably the author of the question has already solved the issue, I leave here my solution, just in case, it could help someone else.
As explained in the question, you need a kind of real-time &quot;smoother&quot; for the trajectory. You are going to have trade-offs: speed, latency, energy efficiency, etc.
I propose to use Alpha-Beta filters, Moving Average Filters or some kind of Adaptative Average filter. They should be faster, easy to implement and with less latency than Kalman filter or similar. I have made a couple of tests, trying to reproduce the type of data used in the question, and testing those filters with quick(and nasty) own implementations. The results are shown below in the next figures:


Cheers.
P.D. Probably, the vibration noise commented in the original question is not absolutely uncorrelated. The data I have generated is using random noise.