Mobile robot localization by geometric hashing and model-based scene matching

Abstract

This paper describes a new technique for determining the initial location and orientation of an indoor mobile robot by geometric hashing and model-based scene matching. The indoor scenes are first modelled off-line in hashing tables using geometric invariants of some special model edge points. Model-based scene matching is completed in three stages. (1) extraction of scene image features and derivation of the the geometric invariants from these features in robot-centered coordinates, (2) finding the best matched candidate and the corresponding transformation using geometric hashing and a weighted distance voting criterion, and (3) the verification of the match by back-projection of model features onto the intensity image of the scene. Matching efficiency is increased substantially by restricting the number of bases through the ordering of image features and the concurrence of features during geometric hashing. Experimental results show that the proposed method is quite efficient and reliable.