Tag Archives: muCSense

Implementing the Gauss-Newton Algorithm for Sphere Fitting (3 of 3)

The first post in this series made it clear that the major computational and storage costs to implementing the Gauss-Newton algorithm come in computing the matrices and . By carefully avoiding materialization of the Jacobian matrix and the residual vector, … Continue reading

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Implementing the Gauss-Newton Algorithm for Sphere Fitting (2 of 3)

I sketched a naïve implementation of the Gauss-Newton algorithm for sphere fitting, and provided an implementation in Octave. While it works fine on a laptop, it uses far too much memory to handle more than a handful of calibration samples … Continue reading

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Implementing the Gauss-Newton Algorithm for Sphere Fitting (1 of 3)

In some calibration strategies we encounter a sphere fitting problem: we need to find the map that does the best job sending the observed data to a unit sphere. This simple problem statement leaves two critical questions unanswered. What family … Continue reading

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muCSense: Using Calibration

I just added some new code to the muCSense library to help calibrate accelerometers and magnetometers. I plan to use the framework to add calibrators for gyros and other sensors too. In this post, I’ll walk through an example sketch … Continue reading

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muCSense: Introduction and Example

In my last post I walked through the steps you need to take to establish a simple connection with the three sensors on SparkFun’s 9DoF Sensor Stick. If you took those code snippets, dumped them into one file, and ran … Continue reading

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