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Feedback Information Expression and Fusion Method for Human-Robot Interaction

机译:反馈信息表达式和人机交互的融合方法

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On the basis of analyzing the information fusion method for human-robot interaction, a kind of information feedback structure for human - robot interaction platform has been provided, the source feedback information is handled with multi-layer processed structure, and the processed multi-mode information is integrated with certain interactive rules and knowledge in interaction knowledge database. A set of feedback information expression and fusion method has been presented in information integration process, the abstract information from feedback multimodality is expressed by the situation of task execution process and the stability of feedback modality, and then these information is fused in light of the result of task execution, at last, the fusion result is delivered to user by the most stable feedback modality. Some experiments have been done with the provided methods in the human-robot interaction system, and parts of the experiment results show that user's cognition loads can be decreased by this semantic information fusion and feedback method, moreover, high work efficiency also can be gotten in human-robot interaction.
机译:在分析人体机器人交互的信息融合方法的基础上,已经提供了一种用于人机交互平台的信息反馈结构,源反馈信息用多层处理结构处理,并处理了多模信息与交互知识数据库中的某些互动规则和知识集成。在信息集成过程中呈现了一组反馈信息表达式和融合方法,反馈多模的抽象信息由任务执行过程的情况和反馈模态的稳定性表示,然后根据结果融合这些信息任务执行最后,融合结果是通过最稳定的反馈方式向用户传递给用户。已经在人机交互系统中提供了一些实验,并且实验结果的一部分表明,通过该语义信息融合和反馈方法可以降低用户的认知载荷,而且可以在高效效率下降人机互动。

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