Hybrid Global Positioning System-Adaptive Neuro-Fuzzy Inference System based autonomous mobile robot navigation

Abstract

The collision-free navigation of a mobile robot in clutter environments is challenging. Global Positioning System (GPS) and adaptive neuro-fuzzy inference system (ANFIS) are well-known techniques widely used for navigation and control, respectively. This paper proposes a hybrid GPS-ANFIS based method for collision-free navigation of autonomous mobile robots. The GPS-based controller keeps the navigation direction of the robot toward the static or dynamic target. It uses the coordinates received from the two GPS modules on the edges of the longitudinal axis of the robot all together with the coordinates of the target to divert it from the current path making a certain angle towards the target. The performance of the proposed method in navigating a mobile robot in clutter environments and its effectiveness in comparison with the other collision-free navigation methods has been evaluated through simulations. The evaluation criteria are on the basis of the obstacle avoidance behavior and the length of the discovered collision-free path by the robot. The results have shown that our hybrid GPS-ANFIS method navigates the robot toward the goal via a shorter path while avoiding the obstacles.