系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (10): 3313-3324.doi: 10.12305/j.issn.1001-506X.2025.10.18

• 系统工程 • 上一篇    

基于人机协同作战多通道交互系统的隐性知识挖掘

王名珺1,2, 吴晓莉1,2,*, 晏彪1,2, 张欣悦1,2, 武愈涵1,2   

  1. 1. 南京理工大学设计艺术与传媒学院,江苏 南京 210094
    2. 语言信息智能处理及应用工信部重点实验室,江苏 南京 210094
  • 收稿日期:2024-06-17 出版日期:2025-10-25 发布日期:2025-10-23
  • 通讯作者: 吴晓莉
  • 作者简介:王名珺(2000—),女,硕士研究生,主要研究方向为人因与人机交互
    晏 彪(1996—),男,博士研究生,主要研究方向为人机交互
    张欣悦(2001—),女,硕士研究生,主要研究方向为多通道交互设计
    武愈涵(2001—),女,硕士研究生,主要研究方向为人机交互
  • 基金资助:
    江苏省自然科学基金(BK20221490); 国家自然科学基金(52175469)资助课题

Tacit knowledge mining based on multi-channel interactive system of human-machine cooperative combat

Mingjun WANG1,2, Xiaoli WU1,2,*, Biao YAN1,2, Xinyue ZHANG1,2, Yuhan WU1,2   

  1. 1. School of Design Arts and Media,Nanjing University of Science and Technology,Nanjing 210094,China
    2. Key Laboratory of Ministry Industry and Information Technology for Language Information Processing and Applications,Nanjing 210094,China
  • Received:2024-06-17 Online:2025-10-25 Published:2025-10-23
  • Contact: Xiaoli WU

摘要:

在人机协同作战场景下,针对如何通过多通道交互关联隐性知识以优化交互设计问题,提出隐性知识挖掘方法。首先,分析典型人机协同作战任务中的作战流程,结合视觉、语音、手势等多种交互通道,设计协同作战的多通道人机交互系统。其次,以该系统为载体,构建行为认知图模型,对协同作战流程中的关键节点进行关联度分析,并结合眼动追踪数据对操作者的交互行为进行定量分析。最后,引入图论中的物理量对隐性知识进行显性化描述,表明所提方法可有效融合感知信息。所提方法可为多通道交互系统中人机交互模式的优化设计提供有价值的参考。

关键词: 人机协同, 多通道交互, 隐性知识, 眼动追踪

Abstract:

In the context of human-machine cooperative combat, a method for tacit knowledge mining is proposed aiming at optimizing interaction design problem through multi-channel interactive association tacit knowledge. Firstly, the operational process of typical human-machine cooperative combat tasks is analyzed, and a multi-channel interactive system of human-machine is designed by integrating multiple interaction channels such as vision, speech, and gestures. Secondly, based on the proposed system, a behavioral-cognitive graph model is constructed to analyze the association between key nodes in the cooperative task process. And eye-tracking data is employed to quantitatively assess the operator interactive behavior. Finally, physical quantities from graph theory are introduced to explicitly describe the tacit knowledge, demonstrating that the proposed method effectively integrates perceptual information. The proposed method provides a valuable reference for optimizing human-machine interactive patterns in multi-channel systems.

Key words: human-machine cooperative, multi-channel interaction, tacit knowledge, eye-tracking

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