The effects of partial observability in SLAM

In this article, we show that partial observability hinders full reconstructibility of the state space in SLAM, making the final map estimate dependent on the initial observations, and not guaranteeing convergence to a positive semi-definite covariance matrix. By characterizing the form of the total Fisher information we are able to determine the unobservable state space directions. To overcome this problem, we formulate new fully observable measurement models that make SLAM stable.