The goal here is to have a predictive model to check the “health” of subsystems by analyzing logs. this will potentially help with checking for mechanical problems more efficiently.
using pytorch I train an mlp (multi layer perceptron) on features such as system velocity, system position, and supply voltage, with an output (label) of acceleration of the system for example. with this we can compare the real
acceleration and prediction, and tell weather or not the system is ok.
I made it so you can choose the input and output variables to analyze from the wpilogs given, and can also choose the layer sizes of the model.
by clicking calculate we train the model
then we can test any wpilogs from the toTest folder
test outcomes:
“healthy system”: R^2 Score: 0.7926
“broken system (by limiting supply current to quite low)”: R^2 Score: -0.5637
“even more broken (limiting supply current more)”: R^2 Score: -0.8172
Im interested to see if anyone has ideas for this and to hear thoughts
you will need to manuallu put wpi logs into the corrent folders for now