Laser Scan Matching by FAST CVSAC in Dynamic Environment

Abstract

Localization and mapping are very important for safe movement of robots. One possible way to assist with this functionality is to use laser scan matching. This paper describes a method to implement this functionality. It is based on well-known random sampling and consensus (RANSAC) and iterative closest point (ICP). The proposed algorithm belongs to the class of point to point scan matching approach with its matching criteria rule. The performance of the proposed algorithm is examined in real environment and found applicable in real-time application.