DRU: Analysis of Current HAZMAT Response Capabilities and the Impact of Human Robot Interaction on Risk Mitigation

我们的研究解决了如何设计人-机器人交互(HRI)来在动态、不确定和高风险的情况下帮助决策者团队的问题，这些情况需要快节奏的决策。我们目前的研究重点源于我们在HRI领域的工作。我们一直在研究一个人和一个机器人如何协同工作，以解决安全关键应用中的问题，例如在机器人辅助的城市搜索和救援(USAR)环境中；特别是，我们一直在研究HRI设计如何帮助人类决定在不久的将来采取什么行动，特别是在人类操作员看不到机器人的情况下。这样的“远程”机器人操作本身就很困难，因为当机器人在环境中移动时，人类必须完全依赖于在不断变化的参照系中提供的信息。在我们的研究进程中，下一个合乎逻辑的步骤是检查团队决策。为了研究多人/单机器人环境下的决策动态，我们将检查危险材料(危险物质)的处理。就像USAR一样，危险物质通常需要一个机器人远离它的操作员。我们的工作将开发出在正确的时间呈现正确信息的方法：这是面临压力的决策者的永恒目标。到目前为止，许多机器人界面都是由机器人专家为机器人专家设计的。随着机器人的商业化程度越来越高，人们开始更多地关注让预期的最终用户能够使用界面。然而，据我们所知，以前没有人利用社会科学技术来确保机器人信息消费者的需求得到满足。这项研究汇集了来自机器人学、人机交互、决策支持和社会科学社区的研究人员。这种多学科的方法将使我们能够考虑人们如何彼此互动，在快速变化的情况下需要哪些类型的信息，以及我们如何评估和展示风险。在整个项目中，我们将直接与目标用户、第一响应者和决策者合作。现有的机器人系统将在与急救人员的演习中使用，向他们介绍当前的最先进技术，为快速采用提供潜力。危险物质领域的发现也将适用于USAR情况，如地震、飓风和恐怖袭击。

Our research addresses the question of how human-robot interaction (HRI) could be designed to assist teams of decision-makers in the face of dynamic, uncertain, and risky situations, where fast-paced decisions are required. Our current research focus grew out of our work in the HRI domain. We have been studying how one person and one robot work together to solve problems in safety-critical applications, such as in a robotic-assisted urban search and rescue (USAR) context; in particular, we have been examining how the HRI design can help the human decide what actions to take in the near future, especially in cases where the human operator cannot see the robot. Such "remote" robot operation is inherently difficult because the human must rely solely on information presented in a constantly changing frame of reference as the robot moves through the environment. The next logical step in our research progression is to examine team decision-making. To study decision-making dynamics in a multi-human/single-robot context, we will examine hazardous material (HAZMAT) handling. As with USAR, HAZMAT typically requires a robot to be deployed away from its human operator.Our work will develop methods for presenting the "right information at the right time": the perennial goal of the decision-maker under pressure. To date, many robotic interfaces have been designed by roboticists, for roboticists. With robots becoming more commercialized, more attention is starting to be paid to making interfaces usable by the intended end users. We know of no previous efforts, however, to use social science techniques to ensure that the needs of robot information consumers are met. This study brings together researchers from the robotics, human-computer interaction, decision support, and social science communities. This multidisciplinary approach will allow us to consider how people interact with one another, the types of information that are needed in rapidly changing situations, and how we can assess and display risk. We will work directly with the intended users, the first-responders and decision-makers, throughout the project. Existing robot systems will be used in exercises with first-responders to introduce them to the current state of the art, offering the potential for rapid adoption. Findings in the HAZMAT domain will also be applicable to USAR situations such as earthquakes, hurricanes, and terrorist attacks.