A Scan Matching Method using Euclidean Invariant Signature for Global Localization and Map Building

摘要

This paper presents a new scan matching method for mobile robot localization and mapping. The proposed method is based on the geometric hashing scheme, which utilizes Euclidean invariant features in order to match an input scan with reference scans without an initial alignment The method is applicable to global localization in an environment having curved objects. Experimental results show that a map of a large cyclic environment was built with high accuracy using the proposed method.