Fuzzy-Neuro based Navigational Strategy for Mobile Robot

Abstract

Abstract — A new paradigm of intelligent navigation system for mobile robot has been enriched with some common features like: criteria for optimal performance and ways to optimize design, structure and control of robot. With the growing need for the deployment of intelligent and highly autonomous systems, it would be beneficial to flawlessly combine robust learning capabilities of artificial neural networks with a high level of knowledge interpretability provided by fuzzy-logic. Fuzzy-neural network is able to build comprehensive knowledge bases considering sensor-rich system with real time constraints by adaptive learning, rule extraction and insertion, and neural/fuzzy reasoning. This technique is simulated and also compared with other simulation studies by previous researcher. The training for back propagation algorithm and its navigational performances analysis has been done in real experimental setup. As experimental result matches well with the simulation result, the realism of method is verified.