Multilayer Decision-Based Fuzzy Logic Model to Navigate Mobile Robot in Unknown Dynamic Environments

The investigation into mobile robot navigation under uncertain dynamic environments is of great significance. This paper seeks to solve the current problems which are the difficulty to plan in indeterminate ever-changing environments, the problem of optimality, failure in complex situations, and the problem of predicting the obstacle velocity vector. The objective of this study is to propose a multilayer decision-based fuzzy logic model to find the solution for robot navigation through a safe path while preventing any types of barriers and to understand the non-collision mobile robots’ movement in an unknown dynamic environment. In this study, the prediction and priority rules of a multilayer decision are used by the fuzzy logic controller to improve the quality of the next position with regard to its path length, safety, and runtime. The results of comparison studies revealed a considerable improvement in failure rate and path length. Outcomes show that the suggested method displays attractive features, for instance, great stability, great optimality, zero failure rates, and low running time. The average path length for all test environments is 13.11 with 0.47 a standard deviation that provides 89% of an average optimality rate. The average running time is about 5.31 s with a 0.25 standard deviation.