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首页> 外文会议>Unmanned Systems Technology IX; Proceedings of SPIE-The International Society for Optical Engineering; vol.6561 >An agent-based approach to decluttering the interfaces of multi-UAV command and control systems
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An agent-based approach to decluttering the interfaces of multi-UAV command and control systems

机译：基于代理的多UAV命令和控制系统接口整理方法

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摘要

Information overload and cluttered user interfaces can lead to decreased situational awareness and lowered performance of human operators. Irrelevant data increases searching times for tasks requiring the identification of threats, causing delayed decisions. Cognitive burden on the user increases as displays become more cluttered, which results in increased operator stress leading to poor decision-making ability. To address this issue, we have designed an intelligent agent based system for the automatic de-cluttering of a representative net-centric interface designed for controlling multiple unmanned aerial vehicles (UAVs) by a single operator. Our concept is called ARID, for Agent-based Reduction of Information Density. The ARID hypothesis is that intelligent agents can improve operator performance by de emphasizing those aspects of a display that can be inferred as less-important to the mission goals. ARID agents receive information about the world via data feeds provided by various net-centric sources. Each agent has an understanding of the user interface symbols that are used to represent various entities, terrain features, and zones. The agent also is provided with a mission goal which is used for inferring the relevance of a given symbol to the success of the mission goal. First level facts, such as spatial relationships, are calculated by supporting agents and assigned a BDU (belief/disbelief/uncertainty) value. A dynamic set of rules provides an inference mechanism by which an agent can infer new facts from the given assertions. We have developed a Subjective Logic-based Evidential Reasoning Network that explicitly deals with belief and uncertainty in the knowledge base, and is used to derive a relevancy belief for every UI symbol in the map display. Subjective Logic is used to combine values when different sources provide different results for the same symbol. User Interface agents apply the results of the relevancy beliefs and transform the display to minimize the apparent clutter caused by less relevant elements. Two transformations, transparency and grouping, are used in the current implementation.
机译：信息过载和混乱的用户界面可能会导致态势感知降低以及操作员的性能下降。不相关的数据会增加需要识别威胁的任务的搜索时间，从而导致决策延迟。随着显示器变得更加混乱，用户的认知负担增加，这导致操作员压力增加，导致决策能力较差。为了解决这个问题，我们设计了一个基于智能代理的系统，该系统用于自动整理具有代表性的以网络为中心的接口，该接口旨在由一个操作员控制多个无人驾驶飞机（UAV）。我们的概念称为ARID，用于基于代理的信息密度降低。 ARID的假设是，智能座席可以通过不强调显示中可能被认为对任务目标不太重要的那些方面来提高操作员的绩效。 ARID代理通过各种以网络为中心的来源提供的数据提要来接收有关世界的信息。每个代理都了解用于表示各种实体，地形特征和区域的用户界面符号。代理还被提供了任务目标，该任务目标用于推断给定符号与任务目标的成功的相关性。诸如空间关系之类的第一级事实由支持代理计算，并分配了BDU（信任/怀疑/不确定性）值。动态规则集提供了一种推理机制，代理可以通过该机制从给定的断言中推断出新的事实。我们已经开发了基于主观逻辑的证据推理网络，该网络可显式处理知识库中的信念和不确定性，并用于为地图显示中的每个UI符号派生相关信念。当不同的源为同一符号提供不同的结果时，将使用主观逻辑来组合值。用户界面代理应用相关性信念的结果并转换显示，以最大程度地减少由相关性较低的元素引起的外观混乱。当前实现中使用了两个转换，透明性和分组性。

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