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MST-based SOFM in hybrid robot architecture

机译:混合机器人体系结构中基于MST的SOFM

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This paper presented a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it leams topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provided real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework was verified by simulation.
机译:本文提出了一种用于移动机器人导航的集成计划和控制框架。与现有的混合体系结构不同,它使用基于MST(最小生成树)的SOFM(自组织特征图)算法从世界地图中提取拓扑图。高级计划模块将简单任务计划到低级控制模块,低级控制模块将环境信息反馈到高级计划模块。这种方法允许高级和低级模块之间的紧密集成,从而提供实时性能以及对外部环境及其不可预见的变化的强大适应性和反应性。仿真验证了该框架的有效性。

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