Scan matching in a probabilistic framework
Andrea Censi · 2006
We describe an interpretation of scan matching as a probability distribution approximation problem and we propose an algorithm that, employing a particle approximation to the target distribution, can take advantage of the knowledge of the evolution model and provide an estimate of the matching uncertainty. Experiments show it can work in unstructured environments, it is reliable to severe sensor occlusions and it handles under constrained situations gracefully