GCR: Community-Embedded Robotics: Understanding Sociotechnical Interactions with Long-term Autonomous Deployments

该项目结合了人机交互、人为因素、组织沟通、科学技术研究、团队科学和研究信息学等领域的方法和专业知识，以实现对社区和自主机器人交叉现象的持续访问，否则这些现象是不切实际或不可能获得的。研究结果将确定并解决多用途机器人部署到社区时产生的伦理、隐私和安全问题。该研究计划将多个科学领域的变革性扩展到一个共享的研究对象上：社区机器人遭遇。具体来说，目标是扩展机器人和人机交互的人为因素领域，超越传统的关注机器人遇到少量人类，在偶然性或基于事件的暂时性，以及超出实验室环境的限制。这种扩展将使人们能够在现实环境中纵向研究与自主机器人互动的大型、不断变化的人类群体。这项工作将允许机器人感知领域的长期自主扩展其范围，超越建筑环境中的导航挑战和相对可预测的车辆运动，也包括行人行为。所有三个机器人子领域都将为机器人行为的重要方面做出贡献，这些方面只能在现实条件下进行测试，包括人群中的社交导航，社区空间中的安全和信任，以及对机器人能力的内省感知。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project combines methods and expertise in the fields of human-robot interaction, human factors, organizational communication, science and technology studies, team science, and research informatics to achieve sustained access to phenomena at the intersection of communities and autonomous robots that is otherwise impractical or impossible to obtain. The research outcomes will identify and address ethical, privacy, and safety concerns created when multi-purpose robots are deployed into communities. The research plan enables transformative expansions of several scientific fields onto a shared research object: community-robot encounters. Specifically, the goal is to expand the fields of human factors for robotics and human-robot interaction beyond their traditional focus on robots encountering small numbers of humans, in episodic or incident-based temporalities, and beyond the confines of laboratory environments. This broadening will enable studying large, changing groups of humans interacting with autonomous robots longitudinally, in real-world environments. This work will allow the field of robot perception for long-term autonomy to expand its scope beyond the navigational challenges in the built environment and the relatively predictable movement of vehicles to also include pedestrian behavior. All three robotics subfields will contribute to important aspects of robotic behavior only testable in real-world conditions, including social navigation through crowds, safety and trust in community spaces, and introspective perception of robotic capabilities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.