Perception-Based Self-Localization Using Fuzzy Locations

We describe a fuzzy-based approach to self localization to support indoor robot navigation. Our approach is perception-based: clues extracted by the perceptual apparatus are matched against an approximate map to obtain an estimate of the robot's location in the map. Each perceptual clue is treated as a source of partial locational information, represented by a fuzzy set; other sources, like odometry or external measurements , are also treated in this way. Information coming from diierent sources is combined using a fuzzy aggregation operator. We illustrate our approach by showing experiments performed on a mobile robot, Flakey.