Artificial Neural Fuzzy Logic Algorithm for Robot Path Finding

Abstract

One of the major challenges of the autonomous navigation for mobile robots is the detection and avoidance of static and dynamic obstacles in the robot's movement. This problem can be solved by applying different methods or algorithms in order to achieve optimal results. Besides optimizing, attention should be paid also to the processing time of the signals from the sensors, as it relates to the time response of the system as a whole in order to detect and avoid obstacles without colliding them. In this paper we mixed, Fuzzy Logic Controller (FLC-Sugeno) and Artificial Neuronal Fuzzy Logic (ANFL). The proposed approaches are tested in simulation environment as well as on the real mobile robot with satisfying results in terms of paths and processing-time.