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Hierarchical Fuzzy Petri Nets Approach of Simultaneous Task Assignment for Autonomous Mobile Robots

机译:自主移动机器人同时任务分配的分层模糊Petri网途径

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Task assignment processes and its control implying reasoning about objects and resources and their changing states are dominated by discrete or stochastic-event dynamics or both. Estimating the components position of the mobile robot provided by sensor generates unknown, hidden variables which will be model by the means of probabilistic inference taking into account incomplete and uncertain information. The modeling technique proposed in this paper, managing the uncertainty, vagueness and imprecision, bridges the aspects of Petri net theory, as a tool for the representation dynamic discrete event systems, with efficiency of fuzzy rule based reasoning by means of Hierarchical Fuzzy Petri Nets. A case study regarding a reasoning mechanism and an explanation of the reasoning process through task assignment in mobile robot system is explored.
机译:任务分配过程及其控制意味着对对象和资源的推理以及其变化状态是由离散或随机事件动态或两者的主导。估计由传感器提供的移动机器人的组件位置产生未知的隐藏变量,这将是通过考虑不完整和不确定的信息的概率推理的模型。本文提出的建模技术,管理不确定性,模糊和不精确,桥接Petri网理论的方面,作为表示动态离散事件系统的工具,具有基于分层模糊Petri网的模糊规则的推理。探讨了通过移动机器人系统任务分配的推理机制和推理过程解释的案例研究。

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