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

University Of Texas At Austin, Austin TX

Investigators

Abstract

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.