Title :
Adaptive T-S type rough-fuzzy inference systems (ARFIS) for mobile robot navigation
Author_Institution :
Sch. of Comput. Security & Sci., Edith Cowan Univ., Mt Lawley, WA, Australia
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.
Keywords :
fuzzy control; fuzzy reasoning; mobile robots; path planning; rough set theory; uncertain systems; ARFIS; adaptive T-S type rough-fuzzy inference systems; control behavior; control methods; control scheme; fuzzy logic system; mobile robot navigation; mobile robotics; rough set theory; rough-fuzziness; rough-fuzzy controller; uncertainty reasoning process; Fuzzy systems; Mobile robots; Navigation; Robot sensing systems; Trajectory; Uncertainty; T-S type fuzzy systems; fuzzy sets; mobile robot navigation; rough sets; rough-fuzzy hybridization;
Conference_Titel :
Control Automation and Systems (ICCAS), 2010 International Conference on
Conference_Location :
Gyeonggi-do
Print_ISBN :
978-1-4244-7453-0
Electronic_ISBN :
978-89-93215-02-1
