I built EKF and UKF SLAM algorithms. The problem is that I expected to see a difference because of the more precise approximation of the system in the UKF.
Here's a screenshot from the estimated path from both filters [sorry about the German]:
As you can see, the differences are very minor and sum up to an equal performance of both filters within the mean errors for every estimated state. I thought increasing the system noise for a bigger uncertainty would make the advantages of the UKF clearer but it didn't make a difference.
UKF Parameters: $\alpha$: 0.01, $\kappa$: 0, $\beta$: 0.
My question is, what could be the reason for the similiar results of both filters and how can we enhence the UKF performance?
Nvm, the result improved with UKF parameters from a backup. The parameters where to low. New Parameters: $\alpha$: 0.5, $\kappa$: 25, $\beta$: 2.
Mean error X-Position
mean error Y-Position
Mean error orientation