Abstract
This paper presents a technique of path planning of a mobile robot using artificial neural network, fuzzy logic and genetic algorithm. The artificial neural network (ANN) is trained to choose a path from a set of n paths for the mobile robot to move ahead towards the destination. Fuzzy logic (FL) is used to avoid collisions when all the n paths are blocked by obstacles. Genetic Algorithm (GA) is used as optimizer to find optimal locations along the obstacle-free directions and positions by selecting a set of fuzzy rules for the fuzzy logic system from a large rule base. Results show that the combination of these features is computationally efficient by helping each other to eliminate their individual limitations.