Obtaining a fuzzy controller with high interpretability in mobile robots navigation

Abstract

The work presents the design of a fuzzy controller for the wall-following behavior in mobile robotics using the COR (cooperative rules) methodology with ant colony optimization. The system has been tested in several simulated environments using the Nomad 200 robot software, and compared with other controller based on genetic algorithms. The proposed approach obtains a highly interpretable knowledge base in a reduced time, and the designer only has to define the number of membership functions and the universe of discourse of each variable.