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Fuzzy Based Mobile Robot Navigation in an Unknown Environment
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Fuzzy logic has been introduced to deal with uncertain problems. A fuzzy logic controller can be regarded as an expert system that is able to process quality variable and to infer crisp values out of uncertainty. Autonomous Mobile Robot Navigation in an unknown environment is explained in this paper by optimized fuzzy logic algorithm. A mobile robot, having to navigate purposefully from a start location to a target location, needs two basic requirements: sensing and reasoning. However, the pervasive presences of uncertainty in sensing makes the choice of a suitable tool of reasoning and decision making, that can be deal with incomplete information, vital to ensure a robust control system.
This paper first explains what uncertainty in mobile robot navigation in unknown environments is, it proposes a fuzzy logic approach to secure a collision free path avoiding multiple static obstacles; where the robot is the only moving object. The most peculiar aspects of the proposed are in decreasing the number of fuzzy rules and in optimizing the choice of fuzzy sets parameters, rules, and memberships. The algorithm adopts fuzzy logic subsets and memberships to endow the robot with an ability to take decision despite of environmental uncertainties.
This paper first explains what uncertainty in mobile robot navigation in unknown environments is, it proposes a fuzzy logic approach to secure a collision free path avoiding multiple static obstacles; where the robot is the only moving object. The most peculiar aspects of the proposed are in decreasing the number of fuzzy rules and in optimizing the choice of fuzzy sets parameters, rules, and memberships. The algorithm adopts fuzzy logic subsets and memberships to endow the robot with an ability to take decision despite of environmental uncertainties.
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