Mobile Robot Localization Using Fuzzy Segments

This paper presents the development of a framework based on fuzzy logic for multi-sensor fusion and localization in indoor environments. Such a framework makes use of fuzzy segments to represent uncertain location information from different sources of information. Fuzzy reasoning, based on similarity interpretation from fuzzy logic, is then used to fuse the sensory information represented as fuzzy segments. This approach makes it possible to fuse vague and imprecise information from different sensors at the feature level instead of fusing raw data directly from different sources of information. The resulting fuzzy segments are used to maintain a coherent representation of the environment around the robot. Such an uncertain representation is finally used to estimate the robot position. The proposed multi-sensor fusion localization approach has been validated with a mobile platform using different range sensors.