From b6fb95247b8711b8a56c993f172ea0942fb03ae8 Mon Sep 17 00:00:00 2001 From: bresch Date: Mon, 7 Aug 2023 15:36:33 +0200 Subject: [PATCH] ekf2_derivation: fix typo --- src/modules/ekf2/EKF/python/ekf_derivation/derivation.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/modules/ekf2/EKF/python/ekf_derivation/derivation.py b/src/modules/ekf2/EKF/python/ekf_derivation/derivation.py index 6bcc542c4f..83b20495db 100755 --- a/src/modules/ekf2/EKF/python/ekf_derivation/derivation.py +++ b/src/modules/ekf2/EKF/python/ekf_derivation/derivation.py @@ -117,8 +117,8 @@ def predict_covariance( var_u = sf.Matrix.diag([d_vel_var[0], d_vel_var[1], d_vel_var[2], d_ang_var, d_ang_var, d_ang_var]) P_new = A * P * A.T + G * var_u * G.T - # Generate the equations for the lower triangular matrix and the diagonal only - # Since the matrix is symmetric, the upper triangle does not need to be derived + # Generate the equations for the upper triangular matrix and the diagonal only + # Since the matrix is symmetric, the lower triangle does not need to be derived # and can simply be copied in the implementation for index in range(State.n_states): for j in range(State.n_states):