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

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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.