Use of viewpoint planning for fast succinct map matching

Map matching, the ability to match a local map built by a mobile robot to previously built maps, is crucial in robot vision applications. In this paper, we propose a novel map descriptor, to facilitate fast succinct text-based map matching. Unlike previous bag-of-words approaches that trade discriminativity for viewpoint invariance, we develop a holistic view descriptor that is view-dependent and highly discriminative. Because the success of our holistic view descriptor depends on the assumption that the viewpoint is unique given a local map, we also address the issue of viewpoint planning and present a solution that provides similar views for similar local maps. The results of experiments conducted verify the efficacy of our proposed approach.