Explaining Autonomous Decisions in Swarms of Human-on-the-Loop Small Unmanned Aerial Systems

Ankit Agrawal, J. Cleland-Huang
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引用次数: 8

Abstract

Rapid advancements in Artificial Intelligence have shifted the focus from traditional human-directed robots to fully autonomous ones that do not require explicit human control. These are commonly referred to as Human-on-the-Loop (HotL) systems. Transparency of HotL systems necessitates clear explanations of autonomous behavior so that humans are aware of what is happening in the environment and can understand why robots behave in a certain way. However, in complex multi-robot environments, especially those in which the robots are autonomous and mobile, humans may struggle to maintain situational awareness. Presenting humans with rich explanations of autonomous behavior tends to overload them with lots of information and negatively affect their understanding of the situation. Therefore, explaining the autonomous behavior of multiple robots creates a design tension that demands careful investigation. This paper examines the User Interface (UI) design trade-offs associated with providing timely and detailed explanations of autonomous behavior for swarms of small Unmanned Aerial Systems (sUAS) or drones. We analyze the impact of UI design choices on human awareness of the situation. We conducted multiple user studies with both inexperienced and expert sUAS operators to present our design solution and initial guidelines for designing the HotL multi-sUAS interface.
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解释人类在循环中的小型无人机系统的自主决策
人工智能的快速发展已经将重点从传统的人类导向机器人转移到不需要人类明确控制的完全自主机器人。这些通常被称为人在循环(HotL)系统。酒店系统的透明度需要对自主行为做出清晰的解释,这样人类就能意识到环境中发生了什么,并能理解为什么机器人会以某种方式行事。然而,在复杂的多机器人环境中,尤其是那些机器人自主和移动的环境中,人类可能很难保持态势感知。向人类提供关于自主行为的丰富解释往往会使他们承受过多的信息,并对他们对情况的理解产生负面影响。因此,解释多个机器人的自主行为会产生一种需要仔细研究的设计张力。本文研究了用户界面(UI)设计的权衡,为小型无人机系统(sUAS)或无人机群提供及时和详细的自主行为解释。我们分析了UI设计选择对人类情境意识的影响。我们与经验不足和专业的sUAS操作员进行了多次用户研究,以展示我们的设计解决方案和设计HotL多sUAS接口的初步指导方针。
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