RAPID: Human-Robotic Interactions During Harvey Recovery Operations

RAPID：哈维恢复操作期间的人机交互

• 批准号: 1760479
• 负责人: Ranjana Mehta
• 金额: $ 11.76万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1760479&HistoricalAwards=false
• 关键词: RAPID; Human; Robotic; Interactions; During

Effective and efficient disaster recovery is necessary for individuals, the community and businesses to return to normal functioning from large-scale disasters, like hurricanes Harvey and Irma. In recent years, unmanned robots have been used to facilitate rescue, response, and recovery and have been found invaluable in these efforts as they can go where humans cannot. Although these robots do not have someone on the vehicle itself, they do require humans to operate them, and little is known about the demands of this technological work environment on the humans during disaster recovery. What is known is that the pilots often work: in high work demand stressful environments; outside (often in the heat, as hurricanes happen in the summer); require ambulation or prolonged standing in awkward postures for extended periods of time; and sometimes these operators live in the affected area themselves and thus maybe experiencing psycho-social stressors due to the disaster. Given the finite number of trained operators, the availability of different types of robots, and the increasing areas of the country needing assessment of damages using robots due to large-scale disasters, there is a critical need to examine naturalistic human/robotic interactions during recovery operations in affected regions. The study will create a fundamental, principled understanding of attributes of collaborations between human and robot teams that are resilient during disaster recovery operations to minimize costly errors and improve effectiveness of future disaster robotics response and recovery operations.This RAPID award will provide critical and timely information on human/robotic interactions during robot-assisted Harvey recovery operations in the Texas Gulf Coast and surrounding locations impacted by flooding. The study will examine recovery operations that focus on inspections of critical infrastructure affected by the flooding and to assist with economic recovery across different types of structures (homes, factories, neighborhoods, etc.). The objectives of this study are to 1) document the relationships between the human (e.g., pilot) and the robot (e.g., unmanned aerial vehicle) to achieve specific recovery tasks (surveillance and inspections) in dynamically changing and unstable environments (e.g., flood-damaged infrastructure); and 2) determine the key contributors of poor human/robotic interactions to provide heuristics/guidelines for improved human/robotic interactions. Both qualitative and quantitative data collection and analyses techniques will be used: video observations to document the gamut of human/robot interactions during recovery operations, perceptions of workload/fatigue, trust in robots, usability, communication, and training gaps through surveys and interviews from the human teams, types and functions of robots used, operator physiological responses, and task productivity metrics. Findings obtained from this study will be rapidly disseminated to appropriate stakeholders (industry, government, public safety) for developing effective best practices in disaster recovery operations.

有效和高效的灾难恢复对于个人、社区和企业从飓风哈维和厄玛等大规模灾难中恢复正常运作是必要的。近年来，无人驾驶机器人已被用于促进救援，响应和恢复，并在这些努力中被发现是非常宝贵的，因为它们可以去人类不能去的地方。虽然这些机器人本身没有人在车上，但它们确实需要人类来操作它们，而且人们对这种技术工作环境在灾难恢复期间对人类的要求知之甚少。已知的是，飞行员经常在以下环境中工作：高工作要求的压力环境;户外（通常在炎热的夏季，如飓风发生）;需要长时间以尴尬的姿势站立或长时间站立;有时这些操作员自己住在受灾地区，因此可能会因灾难而经历心理社会压力。鉴于训练有素的操作人员数量有限，不同类型的机器人可用，以及该国越来越多的地区需要使用机器人评估大规模灾害造成的损失，因此迫切需要在受灾地区的恢复行动中研究自然的人/机器人互动。这项研究将建立一个基本的，对人类和机器人团队之间协作属性的原则性理解，这些团队在灾难恢复操作期间具有弹性，以最大限度地减少代价高昂的错误，并提高未来灾难机器人响应和恢复操作的有效性。该RAPID奖将提供机器人-协助哈维在德克萨斯州墨西哥湾沿岸和周边地区的恢复行动，受洪水影响。该研究将审查恢复行动，重点是检查受洪水影响的关键基础设施，并协助不同类型的结构（家庭，工厂，社区等）的经济恢复。本研究的目的是：1）记录人类（例如，飞行员）和机器人（例如，无人驾驶飞行器）以在动态变化和不稳定的环境中实现特定的恢复任务（监视和检查）（例如，洪水破坏的基础设施）;以及2）确定不良的人/机器人交互的关键因素，以提供用于改进的人/机器人交互的理论/指南。将使用定性和定量的数据收集和分析技术：视频观察记录恢复操作期间人/机器人交互的范围，工作量/疲劳的感知，对机器人的信任，可用性，沟通和培训差距，通过调查和采访人类团队，使用的机器人的类型和功能，操作员生理反应和任务生产力指标。这项研究的结果将迅速传播给适当的利益攸关方（工业、政府、公共安全），以制定灾后恢复行动的有效最佳做法。