FILTER WITH FUZZY LOGIC ESTIMATION BASED SLAM TO REFRAIN FINITE ESCAPE TIME: AN ANALYSIS IN DIFFERENT MOBILE ROBOT MOVEMENT
In this paper, a mobile robot simultaneous localization and mapping (SLAM) in non-Gaussian noise environment is considered. Over pass decade, the famous Extended Kalman Filter (EKF) are aggressively being used in mobile robot based SLAM observation, but its capabilities only limited in Gaussian noise environment. Since the study is to emphasize the application of autonomous mobile robot in a real life application, the environment is imprecise. Despite to this limitation, H∞ Filter (HF) being choose that may provide better solution in non-Gaussian noise environment. However, HF suffer with Finite Escape Time (FET) issue that limits the HF estimation capabilities and may lead to inaccurate estimation result. Hence, in order to pursue the best performance of SLAM, a new H∞ Filter with Fuzzy Logic (FHF) is proposed. A new FHF technique is developed by adding a fuzzy logic rules and fuzzy set in HF innovation stage. The proposed technique applies the information extracted from the HF measurement innovation. The investigation is done in triangular membership. With suitable range of each membership produces the simulation result convinces that FHF effectively capable in reducing the FET from occurring in mobile robot localization and simultaneously improve the estimation between mobile robot and landmarks.