Where to begin…. (#13)

+/- Reworked collection of altimeter related functions into altimeter class
+/- Reworked bno055 class to be imu class with minimal functionality

\- Removed external Kalman filter implementations in favor of own in house version
\- Removed any/unused files
\+ Added buffer logger for when sitting on pad for extended period of time in effort to prevent filling of flash chip
\+ Added heartbeat LED for alive status

1 files changed, 0 insertions, 98 deletions

diff --git a/include/kalmanfilter.hpp b/include/kalmanfilter.hpp
deleted file mode 100644
index 8b9e942..0000000
--- a/include/kalmanfilter.hpp
+++ /dev/null
@@ -1,98 +0,0 @@
-#pragma once
-#include <Eigen/Dense>
-#include <iostream>
-#include <cmath>
-
-using namespace Eigen;
-
-class KalmanFilter {
-
-    private:
-
-        VectorXf state_vector; // x
-        MatrixXf state_covariance; // P
-
-        MatrixXf state_transition_M; // F
-        MatrixXf control_input_M; // B
-        MatrixXf measurement_M; // H
-
-        MatrixXf process_noise_covariance; // Q
-        MatrixXf measurement_covariance; // R
-
-        MatrixXf I; // Identity
-
-        int n; // State Vector Dimension
-        int p; // Control Vector Dimension
-        int m; // Measurement Vector Dimension
-
-        double dt; // timestep
-
-        /**
-         * @brief Initialize all necessary matrices.
-         * 
-         */
-        void matrixInit();
-
-        /**
-         * @brief Update any existing variable elements in your State Transition 
-         * & Control Input matrices.
-         * 
-         */
-        void updateMatrices();
-
-        /**
-         * @brief Predict current State Vector & State Covariance 
-         * given the current control input.
-         * 
-         * @param control_vec The control input to be applied to the
-         * previous State Vector
-         */
-        void prediction(VectorXf control_vec);
-
-        /**
-         * @brief Correct the State Vector & State Covariance predictions
-         * given a related current measurement.
-         * 
-         * @param measurement Current measurement
-         */
-        void update(VectorXf measurement);
-
-    public:
-
-        KalmanFilter();
-        
-        /**
-         * @brief Construct a new Kalman Filter object
-         * Set the sizes of the Filter's user inputs
-         * 
-         * @param state_dim State Vector Dimension. i.e. dim(x)
-         * @param control_dim Control/Input Vector Dimension. i.e. dim(u)
-         * @param measurement_dim Measurement Vector Dimension. i.e. dim(z)
-         * @param dt timestep
-         */
-        KalmanFilter(int state_dim, int control_dim, int measurement_dim, double dt);
-
-
-        /**
-         * @brief Optional function to set a custom initial state for the Filter.
-         * If not called, State Vector & State Covariance are zero-initialized 
-         * 
-         * @param state_vec Initial State Vector
-         * @param state_cov Initial State Covariance
-         * 
-         * @return Whether state initialization was successful
-         */
-        bool setInitialState(VectorXf state_vec, MatrixXf state_cov);
-
-        /**
-         * @brief Perform Kalman Filter operation with given control input vector
-         * and measurement.
-         * 
-         * @param control current control command
-         * @param measurement current measurement
-         * @param dt timestep
-         * 
-         * @return Filtered state vector
-         */
-        VectorXf run(VectorXf control, VectorXf measurement, double _dt);
-};
\ No newline at end of file