Car-Em

A Synthesis-Based Clinically Assistive Robot System for Emergency Medicine

Datos Bibliográficos

ID22190840
AutoresSandhya Jayaraman (0009-0002-0715-6756, University of California San Diego), Andrew Violette (0000-0002-9852-2741, Cornell University), U Lam Lou (0009-0004-5557-9205, University of California San Diego), Sruti Mani (0009-0008-3338-8116, University of California San Diego), Divya Prakash (0009-0005-5657-0111, Austin College), Leslie Oyama (0000-0002-5057-1915, University of California San Diego), Christopher J Coyne (0000-0003-2467-3800, University of California San Diego), Hadas Kress-Gazit (0000-0002-7754-1011, Cornell University), Laurel D Riek (0000-0001-7906-6691, University of California San Diego)
Año2026
Volumen15
Número3
Páginas1-22
Fecha de publicación2026-05-31
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaACM Transactions on Human-Robot Interaction (JOURNAL)
Identificadores de la revistaISSN: 2573-9522 • E-ISSN: 2573-9522
EditorialAssociation for Computing Machinery (ACM) (PUBLISHER)
DOI10.1145/3797263
OpenAlexW7130506277
IdiomaEN
Referencias citadas63

Emergency departments (EDs) are fast-paced, dynamic, safety-critical spaces where clinicians are overworked and underpaid. To support clinicians, researchers are exploring the contextualization and development of clinically assistive robots (CARs) that can assume non-critical tasks to reduce clinician overload. In this article, we introduce Clinically Assistive Robot System for Emergency Medicine (CAR-EM), collaboratively developed with ED clinicians. CAR-EM includes an autonomous robot and a task specification interface. It completes tasks by leveraging control synthesis, a framework that automatically transforms high-level tasks into control while providing guarantees and feedback. We conducted a feasibility study across two different hospital EDs, where interprofessional clinicians tasked the robot to perform patient assessments and item deliveries. Clinicians found the system easy to use, and particularly helpful to offload busywork. This work demonstrates control synthesis as a feasible tool to develop autonomy for robots in safety-critical spaces, and identifies considerations for failure interventions. We also discuss ethical considerations for deploying robots in hospitals, including healthcare worker displacement and work disruption. Thus, our work: (1) highlights the unique requirements of situating robots in real world hospital EDs, and (2) demonstrates a novel approach leveraging guarantees and feedback from control synthesis methods to successfully implement context-specific CAR behaviors. Through this work, we aim to further research for safer and more reliable robots in real world, uncertain environments

Autonomy · Health care · Robot · Robotics · SAFER · Healthcare Technology and Patient Monitoring · Social Robot Interaction and HRI · Soft Robotics and Applications