The Healthcare Robotics Lab at UC San Diego is led by Dr. Laurel Riek. Our research field is human robot interaction, and we design and develop new robotics and embodied AI technologies to support disabled people, healthcare workers, and community members. Our recent work has applications in the areas of neurorehabilitation, dementia caregiving, and emergency medicine.

We adopt a health equity, human-centered, community-driven approach to our work. We center the voices and ideas of people who are marginalized, to help ensure any technology we create is both well-aligned to their needs and reflective of their ideas. We try to avoid technosolutionism by adopting critical health technology design approaches, and are committed to exploring the ethical, legal, and social implications (ELSI) of our research.

You can read more of our recent papers here, and learn more about working in the lab and the kinds of research we do here.

Here are a few recent projects:

• Cognitively assistive robots to support people with dementia/MCI: For the past several years we have been co-designing new technologies to support people with mild cognitive impairment (MCI) as well as those with mid-late stage dementia. This includes social robots that can extend access by supporting cognitive neurorehabilitation at home (Kubota et al. HRI 2023, HRI 2022, HRI 2020), and supporting interactions with care partners (Guan et al., CHI 2021, Moharana et al., HRI 2019). This also includes efforts that explore systems which can engage in long term learning and adaptation (Woodworth et al., MLHC 2018; Wang et al. AISTATS 2021).

• Robots in acute and critical care: We have several projects centered on supporting clinicians and patients in acute care environments, including the emergency department (ED), as well as critical care (e.g., the ICU). Here, we have been designing low-cost, open source telemedical robots that can keep healthcare workers safe, and extend access to patients, particularly those from low-resource settings. (Matsumoto et al., Pervasive Health 2021). We are also designing new methods for understanding clinical team behavior in real time, and use that to inform how robots should act, such as when supporting teams in high-acute situations (Matsumoto et al., HRI 2023, Taylor et al., HRI 2022, ICRA 2021, CSCW 2019).

• Coordination methods to improve autonomy for physically assistive robots: We also do a lot of basic research which informs these domains. For example, some of our recent work focuses on facilitating autonomy - it is important that robots are able to do the right thing, at the right time, and in the right way, especially in safety critical settings. For example, we created a series of methods to model human-human and human robot synchrony that can inform coordinated robot behavior, validated in experimental settings (Iqbal et al., T-AC 2015, T-RO 2016, RA-L 2017, ICRA 2021). We’ve recently been exploring how this can inform robots that are adaptive and responsive in proximate, shared manipulation contexts, to understand human intentionality, and use that to support teams (Matsumoto et al., THRI 2022, AAAI 2022).

• Critical health technology design and ELSI: We are doing a lot of work on critical health technology design. For example. how to engage in value-centric design processes when creating assistive and personalized robots for people with dementia that support their autonomy (Kubota et al., We Robot 2021, Guan et al., CHI 2021), and ways to reflect social models of disability to reframe assistive robotics (Lee and Riek, THRI 2018). We also explore ways to mitigate health technology harms, such as through designing for exit (Bjorling and Riek, We Robot 2022).