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Hybrid Dynamic Fuzzy Cognitive Maps and Hierarchical Fuzzy logic controllers for Autonomous Mobile Navigation

机译:自主移动导航的混合动态模糊认知图和层次模糊逻辑控制器

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摘要

This work is an evolution of a previous work in which we used a knowledge-based system to autonomous navigation area. Two navigation systems are developed: one uses Fuzzy Cognitive Maps (FCM) and the other is based on a Fuzzy Logic Controller (FLC). For the first system, a variant of the classical FCM, named Hybrid-Dynamic Fuzzy Cognitive Maps (HDFCM), is used to model decision tasks and/or to make inference into a mobile navigation context. Fuzzy Cognitive Maps are a tool that model qualitative structured knowledge through concepts and causal relationships. The proposed model allows representing the dynamic behavior of a mobile robot in presence of changes in the environment. A Hierarchical Weighted Fuzzy Logic Controller (HW-FLC) composes the second navigation system. Simulation results are presented allowing a comparison among both systems and showing the ability of the mobile robot to navigate among obstacles in different scenarios (navigation environment). Finally, initial real results with Arduino micro-controller are showed.
机译:这项工作是我们使用基于知识的系统到自主导航区域的先前工作的演变。开发了两个导航系统:一个使用模糊认知地图(FCM),另一个是基于模糊逻辑控制器(FLC)。对于第一系统,用于将混合动态模糊认知映射(HDFCM)命名的传统FCM的变体用于模拟决策任务和/或将推断置于移动导航上下文中。模糊认知地图是一种通过概念和因果关系来模拟定性结构知识的工具。所提出的模型允许在存在环境中的变化时代表移动机器人的动态行为。分层加权模糊逻辑控制器(HW-FLC)组成第二导航系统。提出了仿真结果,允许在两个系统中进行比较并显示移动机器人在不同场景(导航环境)中障碍物中导航障碍物的能力。最后,显示了使用Arduino Micro-Controller的初始实际结果。

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