diff options
Diffstat (limited to 'filter-kalman')
| -rw-r--r-- | filter-kalman/kalman.cpp | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/filter-kalman/kalman.cpp b/filter-kalman/kalman.cpp index 3a0da608..c70093bb 100644 --- a/filter-kalman/kalman.cpp +++ b/filter-kalman/kalman.cpp @@ -112,8 +112,8 @@ void kalman::fill_process_noise_cov_matrix(StateMatrix &target, double dt) const // brownian motion. Unlike standard models for tracking of objects // with a very well predictable trajectory (e.g. // https://en.wikipedia.org/wiki/Kalman_filter#Example_application.2C_technical) - double sigma_pos = s.process_sigma_pos; - double sigma_angle = s.process_sigma_rot; + double sigma_pos = settings::process_sigma_pos; + double sigma_angle = settings::process_sigma_rot; double a_pos = sigma_pos * sigma_pos * dt; double a_ang = sigma_angle * sigma_angle * dt; constexpr double b = 20; @@ -238,7 +238,7 @@ void kalman::filter(const double* input_, double *output_) // We can use this to calculate the size of the deadzone, so that in the stationary state the // deadzone size is small. Thus the tracking error due to the dz-filter becomes also small. PoseVector variance = kf.state_cov.diagonal().head(6); - dz_filter.dz_size = variance.cwiseSqrt() * s.deadzone_scale; + dz_filter.dz_size = variance.cwiseSqrt() * settings::deadzone_scale; } output = dz_filter.filter(output); |