Exploiting prior information in GraphSLAM

Abstract

In this paper we present a general method for exploiting prior information to constrain the location of land marks in GraphSLAM. Prior information can be obtained for many environments in many different ways. However, this information can be incomplete, out-of-date, or presented in a different form than that used by the robot. Therefore, we argue that prior information is most naturally modelled as sets of potential constraints that act between landmarks. We present an extension of GraphSLAM that incorporates these constraints. We illustrate the results in an experiment with a 3D laser scanner and demonstrate a significant improvement in performance.