Robot pose estimation in unknown environments by matching 2D range scans

We develop two algorithms to register a range scan to a previous scan so as to compute relative robot positions in an unknown environment. The first algorithm is used on matching tangent lines defined on two scans and minimizing a distance function. The second algorithm iteratively establishes correspondences between points in the two scans and then solves the point-to-point least-squares problem to compute the relative pose. Our methods avoid the use of localized features. They work in curved environments and can handle partial occlusions.<
>