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EKF right now is 2d, biggest goal is to transition it into 3d
Explore error state kalman filters, not much clear information online
Look into unscented kalman filters (don't need to take jacobian), ideal for parallelization (look into this)
Start with a basic cartesian kalman filter simulation
Read about the bicycle model in order to understand ackermann model, makes assumption that there's no axle between the front wheels
Make a sim with ackermann model and ekf
Do dead reckoning with wheel encoders and steering on mini car to make sure ackermann model makes sense
Incorporate ramps with IMU pitch with above step
Confirm what sensors are available to get data from
Transition into testing the kalman filter I write, will need to tune covariances for the different sensors through trial and error (ex. IMU might be really bad at velocity)
Make sure to set a ground truth when finetuning, ex. tape the course the car will take
Meeting Notes