Fuzzy membership scaling mechanisms for mobile robot behaviours

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Fuzzy behaviours are commonly used in reactive mobile robot navigation strategies, where sensory information is either uncertain or incomplete. However, the complexity of such controllers usually grow exponentially with the number of fuzzy input partitions and rules in the rule base. Furthermore, attempts to reduce the number of input partitions will typically erode the performance of the controllers. This work investigates several membership function scaling mechanisms as an avenue for improving the performance of fuzzy behaviours based on minimal rule base controllers. The configurations are based on the closely-related concepts of linguistic hedges and non-linear scaling. The scaling parameters for the goal seeking and obstacle avoidance behaviours are tuned in simulation via a genetic algorithm optimisation process. The results show that the controller configuration based on input membership function scaling consistently outperforms simple fuzzy logic controllers with the same number of fuzzy input partitions and rules.
Original languageEnglish
Title of host publicationTrends in Intelligent Robotics, Automation, and Manufacturing: First International Conference, IRAM 2012
EditorsS G Poonambalam, Jussi Parkkinen, Kuppan Chetty Ramanathan
Place of PublicationBerlin Heidelberg
PublisherSpringer-Verlag London Ltd.
Pages57 - 66
Number of pages10
ISBN (Print)9783642351969
Publication statusPublished - 2012
EventInternational Conference on Intelligent Robotics, Automation and Maufacturing (IRAM 2012) - Kuala Lumpur, Malaysia
Duration: 28 Nov 201230 Nov 2012
Conference number: 1st


ConferenceInternational Conference on Intelligent Robotics, Automation and Maufacturing (IRAM 2012)
Abbreviated titleIRAM 2012
CityKuala Lumpur

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