A novel neuro-fuzzy system for mobile robot reactive navigation

This paper presents a novel neuro-fuzzy reasoning system for mobile robot to navigate among static obstacles in unknown environment. The proposed approach has the advantage of greatly reducing the number of if-then rules, that could rise when using classical fuzzy systems, by introducing weighting factors for the sensor inputs, thus inferring the reflexive conclusions from each input to the system rather than putting all the possible states of all the inputs to infer a single conclusion. Four simple neural networks are used to determine the weighting factors. Each neural network is responsible for determining the weighting factor for one sensor input. Simulation results are presented to demonstrate the merits of the proposed system.