Probabilistic mapping of an environment by a mobile robot

This paper addresses the problem of building large-scale maps of indoor environments with mobile robots. It proposes a statistical approach that describes the map building problem as a constrained maximum-likelihood estimation problem, for which it devises a practical algorithm. Experimental results in large, cyclic environments illustrate the appropriateness of the approach