SGER: Requirements Assessment for a Multiple Robot-Multiple Human Interface

SGER：多机器人多人机界面的需求评估

• 批准号: 0519421
• 负责人: Julie Adams
• 金额: --
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-15 至 2007-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0519421&HistoricalAwards=false
• 关键词: SGER; Requirements; Assessment; Multiple; Robot

There exist many examples of Human-Robotic Interaction (HRI) for a single robot or a small number of robots (2-4). But HRI development for large robot teams requires novel techniques for presenting large amounts of data so as to support a human's ability to maintain situation awareness while not overloading his/her cognitive capabilities. In this project the PI will assess needs and requirements, and develop preliminary interface designs, for tools that will permit a small number of humans to supervise large robotic teams, a capability not available with current HRI methodologies. To this end, the PI will build on prior work in HCI, CSCW, and complex human-machine systems. She will interact continuously with and solicit feedback from the Metro Nashville Police Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) search and rescue team, because a basic premise of the work is that in order to develop useful interfaces one must first understand how organizations will actually use large teams of robots, which in turn requires an understanding of how the human team currently completes their tasks (without robots), their expectations of a robotic team, and requirements for robotic team capabilities.Broader Impacts: This work will advance the fields of robotics, artificial intelligence, and human factors. Specifically, it will advance the community's understanding of how large numbers of robots can be effectively supervised, managed, and guided by a small number of human operators, thus affording more usable systems while reducing the associated manpower and exposure to potentially dangerous contaminants. Due to the project's focus on deploying robots for CBRNE attacks, the results will have broad affects on developing deployable robotic systems based upon user feedback to meet ever-increasing Homeland Security needs.

对于单个机器人或少量机器人，存在许多人机交互（HRI）的例子（2-4）。但是，大型机器人团队的HRI开发需要新颖的技术来呈现大量数据，以支持人类保持态势感知的能力，同时不会超载他/她的认知能力。在这个项目中，PI将评估需求和要求，并开发初步的接口设计，这些工具将允许少数人监督大型机器人团队，这是当前HRI方法无法提供的能力。为此，PI将建立在HCI， CSCW和复杂人机系统的先前工作基础上。她将不断与纳什维尔地铁警察化学、生物、放射、核和爆炸（CBRNE）搜索和救援团队进行互动并征求反馈，因为这项工作的一个基本前提是，为了开发有用的界面，必须首先了解组织将如何实际使用大型机器人团队，这反过来又需要了解人类团队目前如何完成任务（没有机器人），他们对机器人团队的期望，以及对机器人团队能力的要求。更广泛的影响：这项工作将推动机器人、人工智能和人为因素领域的发展。具体来说，它将促进社会对大量机器人如何由少数人类操作员有效监督、管理和指导的理解，从而提供更多可用的系统，同时减少相关的人力和潜在危险污染物的暴露。由于该项目的重点是部署用于CBRNE攻击的机器人，其结果将对开发基于用户反馈的可部署机器人系统产生广泛影响，以满足不断增长的国土安全需求。