REU Site: Collaborative Human-Robot Interaction

人-机器人交互(Human-Robot Interaction，HRI)有可能影响到几个现实世界的领域，如医院、家庭、学校、办公室或基础设施地点，在这些领域，机器人以独特的方式能够帮助人类团队成员实现共同目标。然而，有效的人-机器人协作存在许多挑战，这些挑战阻碍了这一承诺，例如使用自然语言与人类合作伙伴进行交流，通过可视界面向操作员提供信息，或者快速提供信息以便人能够提供帮助。我们提出了一个HRI方向，为本科生的研究经验提供几个密切相关的项目。项目团队每年夏天将指导10名本科生，从事以下技术领域的直接影响辅助机器人的研究：开发针对护理环境的自主机器人能力，例如与护理专业人员合作执行复杂任务的联网机器人设备，以支持就地老龄化；利用机器人提供技术支持的操作的人类指挥和控制基础设施；以及在利用无线频谱的未使用部分的同时，共同用于关键任务目标的机器人、计算机和嵌入式设备网络的连接和安全。本科生体验研究网站的目标是开发和评估机器人系统，其功能是帮助弥合人与机器人之间的协作差距，并高效有效地实现上述目标。本科生的暑期活动将提供与当前研究项目相关的实践科学和工程活动，以及专业发展，并提供撰写研究生院申请和如何申请奖学金以支持研究生教育的培训课程。该网站将开发新的自主机器人能力和支持网络和数据科学技术，以应对在医院、诊所、家庭和基础设施环境中操作自主系统的现实世界挑战。该网站将为环路中的半自主机器人行为、快速变化的频域中的无线网络连接以及处理大量真实世界数据开发解决方案。拟议的网站提供了与这些计算领域有关的五个项目：社会适当互动的实证研究；基于语言的人-机器人协作；地下采矿环境的自主机器人勘探；多机器人协作和用于安全、准确和可靠检查的人在环中；以及无线环境中不同类型机器人设备的网络管理。这个REU网站通过开发辅助技术这一共同目标将这些项目联系在一起。学生将发展领域知识、数学技能和跨学科能力。该项目可能产生的知识产权将包括对长期人-机器人交互的研究，针对具有挑战性的信号环境的无线联网，用于人-机器人协作的自主机器人能力，以及用于处理来自真实世界系统的大量数据的数据科学工具。

Human-Robot Interaction (HRI) has the potential to affect several real world domains such as hospitals, homes, schools, offices, or infrastructure sites where robots are uniquely able to assist a human team member to achieve a common goal. However, there are many challenges for effective human-robot collaboration that impinge on this promise, such as communicating with human partners using natural language, providing information to an operator through a visual interface, or quickly providing information so that a person is able to offer assistance. We propose an HRI direction that provides several closely-related projects for undergraduate research experiences. The project team will mentor 10 undergraduates each summer, pursuing research directly impacting assistive robotics, in the following technical areas: development of autonomous robot capabilities targeted for care environments, such as networked robotics devices cooperating with care professionals to perform complex tasks in support of aging in place; human command-and-control infrastructure for operations that utilize robots for technology support; and connectivity and security for a network of robots, computers, and embedded devices collectively used to mission-critical goals while utilizing unused parts of the wireless spectrum. The goal of this Research Experiences for Undergraduates (REU) site is to develop and evaluate robotic systems whose function is to help bridge the human-robot collaboration gap and achieve the above objectives efficiently and effectively. The summer activities for undergraduates will provide hands-on science and engineering activities related to current research projects, and professional development with training sessions on writing a graduate school application and how to apply for fellowships to support graduate education. The site will develop new autonomous robot capabilities and supporting network and data science technology to address real-world challenges of operating autonomous systems in hospital, clinic, home, and infrastructure environments. This site will develop solutions for semi-autonomous robot behavior with humans in the loop, wireless network connections in rapidly changing frequency domains, and processing high volumes of real-world data. The proposed site presents five projects related to these computing domains: Empirical Study of Socially-Appropriate Interaction; Language-Based Human-Robot Collaboration; Autonomous Robotic Exploration of Underground Mine Environments; Multi-robot Collaboration and Human in-the-loop for Safe, Accurate and Reliable Inspection; and Network Management of Heterogeneous Robotics Devices in a Wireless Environment. This REU site links these projects together through the common objective of developing assistive technology. Students will develop domain knowledge, mathematical skills, and interdisciplinary competency. The possible intellectual properties resulting from this project will include study on long-term human-robot interaction, wireless networking for challenging signal environments, autonomous robot capabilities for human-robot teaming, and data science tools for processing high volumes of data from real-world systems.