#include <kalman_filter.h>
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| | KalmanFilter (const T *state_transition_data, const T *observation_data, const T *process_covariance_data, const T *default_measurement_covariance_data) |
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| | KalmanFilter (const Eigen::Matrix< T, N, N > &state_transition_matrix, const Eigen::Matrix< T, K, N > &observation_matrix, const Eigen::Matrix< T, N, N > &process_covariance, const Eigen::Matrix< T, K, K > &default_measurement_covariance) |
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| void | Step (State *state) const |
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| void | Update (const Eigen::Matrix< T, K, 1 > &measurement_mean, const Eigen::Matrix< T, K, K > &measurement_covariance, State *state) const |
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| void | Update (State *state, const Eigen::Matrix< T, K, 1 > &measurement_mean) const |
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template<typename
T,
int N,
int K>
class mv::KalmanFilter< T, N, K >
Definition at line 30 of file kalman_filter.h.
◆ KalmanFilter() [1/2]
template<typename
T ,
int N,
int K>
| mv::KalmanFilter< T, N, K >::KalmanFilter |
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const T * | state_transition_data, |
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const T * | observation_data, |
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const T * | process_covariance_data, |
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const T * | default_measurement_covariance_data ) |
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inline |
◆ KalmanFilter() [2/2]
template<typename
T ,
int N,
int K>
| mv::KalmanFilter< T, N, K >::KalmanFilter |
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const Eigen::Matrix< T, N, N > & | state_transition_matrix, |
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const Eigen::Matrix< T, K, N > & | observation_matrix, |
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const Eigen::Matrix< T, N, N > & | process_covariance, |
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const Eigen::Matrix< T, K, K > & | default_measurement_covariance ) |
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inline |
◆ Step()
template<typename
T ,
int N,
int K>
◆ Update() [1/2]
template<typename
T ,
int N,
int K>
| void mv::KalmanFilter< T, N, K >::Update |
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const Eigen::Matrix< T, K, 1 > & | measurement_mean, |
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const Eigen::Matrix< T, K, K > & | measurement_covariance, |
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State * | state ) const |
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inline |
◆ Update() [2/2]
template<typename
T ,
int N,
int K>
The documentation for this class was generated from the following file: