Self-Localization Estimation for Mobile Robot Based on Map-Matching Using Downhill Simplex Method

Abstract

This paper describes a map-matching method which utilizes a downhill simplex method for self-localization estimation of a mobile robot for indoor and outdoor application. Although particle filter is widely established as a method of map-matching, it requires considerable time for recovery when the correct position is unidentifiable. One of the features of the downhill simplex method proposed in this paper is that the search point distribution is wide when it is challenging to determine a point as the correct position. However, it immediately shrinks when the correct position is identified. In this study, it is compared with particle filter and demonstrates the effectiveness of the proposed method through a discussion on the difference between the search methods.