Fuzzy dynamic localization for mobile robots

In this paper, we introduce a new fuzzy logic-based approach for dynamic localization of mobile robots equipped with a ring of sonar sensors. In this approach, the angular uncertainty and radial imprecision of sonar data are modeled by possibility distributions. From sonar data, a local fuzzy composite map is constructed and fitted to the given global map of the environment to identify robotʹs location. As a result of this fit, either a unique fuzzy location or multiple candidate fuzzy locations are obtained. To reduce the multiple candidate locations, the robot is moved to a new location and a new local fuzzy composite map is constructed. Then, a new set of candidate fuzzy locations is obtained. By considering the robotʹs movement, a set of hypothesized locations is identified from the old set of candidate locations. The hypothesized locations are matched with the new candidate locations and the candidates with low degree of match are eliminated. This process is continued until a unique location is obtained. The matching process is performed by using the fuzzy pattern matching technique. The proposed method is implemented on a Nomad 200 robot and the results are reported.