Collaborative Research: FW-HTF-R: The Future of Robot-Assisted Nursing: Interactive AI Frameworks for Upskilling Nurses and Customizing Robot Assistance

Nursing is a discipline of knowledge and practice focused on delivering patient-centered care. As the healthcare providers who are with hospitalized patients 24 hours a day, 7 days a week, registered nurses are crucial for ensuring patient safety and delivering patient-centered care. Alarmingly, however, the U.S. is experiencing a dire nursing shortage, which is projected to significantly worsen in the next decade. As a result, nurses have limited time for patient-centered care. To continue providing high-quality patient care, healthcare leaders are scrambling for solutions, often turning to technological aids such as artificial intelligence (AI) and robots. On one hand, AI-enabled robotic assistants hold the potential to support nurses in some routine tasks, allowing them to spend more time on patient care and improving patient outcomes. On the other hand, the introduction of robots also brings forth several areas of concerns such as increase in nursing workload due to required training and maintenance to use these complex systems. This planning project develops a multi-disciplinary research agenda to systematically introduce nurses to AI-enabled robotics technology, with the goal of ensuring that the integration of robots in the future of nursing brings long-term positive impact.

This work has been supported by grant NSF 2222876.

Related Publications

1. Q. Meng, C. Quintero-Peña, Z. Kingston, V. Unhelkar, and L. E. Kavraki, “Perception-Aware Planning for Robotics: Challenges and Opportunities,” in 40th Anniversary of the IEEE International Conference on Robotics and Automation, 2024.
   
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   BibTeX

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   @inproceedings{meng2024-review,
     author = {Meng, Qingxi and Quintero-Pe{\~n}a, Carlos and Kingston, Zachary and Unhelkar, Vaibhav and Kavraki, Lydia E.},
     title = {Perception-Aware Planning for Robotics: Challenges and Opportunities},
     booktitle = {40th Anniversary of the IEEE International Conference on Robotics and Automation},
     year = {2024},
     abstract = {In this work, we argue that new methods are needed to generate robot motion for
         navigation or manipulation while effectively achieving perception goals. We support our
         argument by conducting experiments with a simulated robot that must accomplish a primary
         task, such as manipulation or navigation, while concurrently monitoring an object in the
         environment. Our preliminary study demonstrates that a decoupled approach fails to achieve
         high success in either action-focused motion generation or perception goals, motivating
         further developments of approaches that holistically consider both goals.}
   }
   

   Abstract

   ×

   In this work, we argue that new methods are needed to generate robot motion for navigation or manipulation while effectively achieving perception goals. We support our argument by conducting experiments with a simulated robot that must accomplish a primary task, such as manipulation or navigation, while concurrently monitoring an object in the environment. Our preliminary study demonstrates that a decoupled approach fails to achieve high success in either action-focused motion generation or perception goals, motivating further developments of approaches that holistically consider both goals.
   Details
2. C. Quintero-Peña, P. Qian, N. Fontenot, H.-M. Chen, S. Hamlin, L. Kavraki, and V. Unhelkar, “Robotic Tutors for Nurse Training: Opportunities for HRI Researchers,” in 2023 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2023.
   
   pdf publisher bibtex abstract details

   BibTeX

   ×

   @inproceedings{quintero2023-robotic-nurse,
     title = {Robotic Tutors for Nurse Training: Opportunities for HRI Researchers},
     author = {Quintero-Pe{\~n}a, Carlos and Qian, Peizhu and Fontenot, Nicole and Chen, Hsin-Mei and Hamlin, Shannan and Kavraki, Lydia and Unhelkar, Vaibhav},
     booktitle = {2023 31st IEEE International Conference on Robot and Human Interactive
         Communication (RO-MAN)},
     year = {2023}
   }
   

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