Indoor fuzzy self-localization using fuzzy segments

Abstract

The research presented in this paper approaches the issue of indoor localization using the fuzzy logic framework for modeling and dealing with the uncertainty of the position measurements. Fuzzy logic presents properties that make it a suitable tool to represent and manage the different factors that affect the measures. This framework allows representing the perceptions, including their associated uncertainty, using fuzzy sets and making use of the tools provided by the framework to manage and operate them. This work uses the fuzzy segment theory to maintain a coherent local representation around the robot using multi-sensor fusion based on fuzzy logic, and uses these fuzzy segments to feed a fuzzy self-localization method, which is able to deal with the ambiguity in the global localization problem.