Fuzzy Inference Approach for Autonomous Ground Vehicle Navigation in Dynamic Environment

In recent years intelligent soft computing technique such as fuzzy inference system (FIS) is proven to be an efficient and suitable when applied to variety of systems. In this paper, we intend to formulate two fuzzy inference systems; sensors based navigation technique for an autonomous vehicle in cluttered dynamic environment. The first FIS controller utilises three sensors based information such as front distance (FD), right distance (RD), left distance (LD) and the second FIS controller employs the angle difference (AD) between the autonomous vehicle's heading and the target angle for choosing the optimal direction while moving towards the target. The simulation experiments have been carried out under three different scenarios to investigate the validation of the proposed FIS controllers. We have presented the simulation experiments using MATLAB software package, showing that the FIS controllers consistently perform navigation task and path planning safely and efficiently in a terrain populated with moving obstacles.