Adaptive T-S type Rough-Fuzzy Inference Systems (ARFIS) for Mobile Robot Navigation

Authors

Chang Su Lee, Edith Cowan University

Document Type

Conference Proceeding

Keywords

T-S type fuzzy systems, fuzzy sets, mobile robot navigation, rough sets, rough-fuzzy hybridization

Publisher

Institue of Control, Robotics and Systems (ICROS)

Faculty

Faculty of Computing, Health and Science

School

School of Computer and Security Science

RAS ID

10233

Comments

Lee, C. (2010). Adaptive T-S type Rough-Fuzzy Inference Systems (ARFIS) for Mobile Robot Navigation. Proceedings of International Conference on Control, Automation and Systems (ICCAS) 2010. (pp. 403-408). KINTEX, Gyeonggi-do, Korea. Institue of Control, Robotics and Systems (ICROS). Available here

Abstract

A new Rough-Fuzzy Controller is proposed to enhance the uncertainty reasoning process in control scheme in mobile robotics. The rough set theory and fuzzy logic system were utilized to calculate the `rough-fuzziness' for inputs from environments. The experimental results showed that the proposed rough-fuzzy controller performed better control behavior compared to other control methods in mobile robot navigation.