A reliable feature matching method in omnidirectional views for autonomous map generation of a mobile robot

Deals with a matching problem of finding correspondences of features in two omnidirectional images. The proposed method combines the advantages of correlation-based matching and dynamic programming to yield reliable matching results. Our method works well even when some features in one image don´t have corresponding features in the other. The search space of the dynamic programming can be reduced by the geometric constraints that the omnidirectional vision sensor provides. We also present a recursive scheme for position estimation of the matched features, so that on-line map generation is possible. Experimental results show that zero failure rate of matching in an indoor environment can be obtained and that a feature-drawing map can be successfully constructed by the proposed feature matching algorithm and map building method