A new smallest sigma set for the Unscented Transform and its applications on SLAM

In this work we propose a new set of sigma points for the Unscented Transform that uses the minimum number of points. We than compare this new set with the symmetric set, the reduced set, and the spherical set. Simulations comparing this sets are done to verify the properties of this set and to verify their transforms. Lastly, we simulate each of these sets in a recursive filter for SLAM. The results show that our set is a better choice for a non symmetric prior distribution and still a good alternative for symmetric prior distributions.