  We present RCareWorld, a human-centric simulation world for physical and
social robotic caregiving designed with inputs from stakeholders, including
care recipients, caregivers, occupational therapists, and roboticists.
RCareWorld has realistic human models of care recipients with mobility
limitations and caregivers, home environments with multiple levels of
accessibility and assistive devices, and robots commonly used for caregiving.
It interfaces with various physics engines to model diverse material types
necessary for simulating caregiving scenarios, and provides the capability to
plan, control, and learn both human and robot control policies by integrating
with state-of-the-art external planning and learning libraries, and VR devices.
We propose a set of realistic caregiving tasks in RCareWorld as a benchmark for
physical robotic caregiving and provide baseline control policies for them. We
illustrate the high-fidelity simulation capabilities of RCareWorld by
demonstrating the execution of a policy learnt in simulation for one of these
tasks on a real-world setup. Additionally, we perform a real-world social
robotic caregiving experiment using behaviors modeled in RCareWorld. Robotic
caregiving, though potentially impactful towards enhancing the quality of life
of care recipients and caregivers, is a field with many barriers to entry due
to its interdisciplinary facets. RCareWorld takes the first step towards
building a realistic simulation world for robotic caregiving that would enable
researchers worldwide to contribute to this impactful field. Demo videos and
supplementary materials can be found at:
https://emprise.cs.cornell.edu/rcareworld/.
