A few days ago I shared a benchmark where FusionCore beat robot_localization EKF on a single NCLT sequence. Fair enough… people called out that one sequence can easily be cherry-picked. Someone also mentioned that the particular sequence I used is known to be rough for GPS-based filters. Others asked if RL was just badly tuned, or how FusionCore could outperform it that much if both are just nonlinear Kalman filters… etc All good questions. So I went back and ran six sequences across different weather conditions. Same config for everything. No parameter tweaks between runs. The config is in fusioncore_datasets/config/nclt_fusioncore.yaml , committed along with the results so anyone can check.…