Performance evaluation of graph-reduction in SLAM through pose rejection

During long-term operation graph-based SLAM methods suffer from unbounded growth of the pose graph and computational cost. To limit the graph size, various methods to reduce the graph have been studied in the past. In this paper we propose a criterion to reject poses, based on the difference between expected and real scan of the candidate. The performance of this reduction method is then evaluated in terms of error and computation time.