Maximum likelihood combining of stochastic maps

The problem of combining stochastic maps obtained by independent agents is considered. Using the generalized likelihood ratio statistics, the problem of matching triangles that correspond to common landmark observations in different stochastic maps is formulated as a bipartite matching problem with generalized likelihood ratio statistics. From the matched triangles between each map, the maximum likelihood combining of stochastic maps is generated. It is shown that the generalized likelihood ratio statistic and the maximum likelihood combining of maps can be computed in closed form, which makes the proposed algorithm a scalable solution to matching and combining stochastic maps with a large number of landmarks.