Affordable Mobile Robots for the Elderly

The goal is to develop in three stages a new affordable robot with the participation of Living Independently for Elders (LIFE) members and clinicians. The robot will be developed by a multidisciplinary team headed by Dr. Yim at University of Pennsylvania (UPENN) (PI), Dr. Tessa Lau at Savioke Corp, and Drs. Johnson and Cacchionne at UPENN PM\&R and UPENN Nursing, respectively. The aim is to build a low-cost robot platform that will focus on the simple, but key, repetitive, data-driven tasks that robots do well. Rather than attempt to create a robot helper that mimics humans, the aim is to free human caregivers from the time-consuming tasks that robots can accomplish with facility, thereby allowing humans to focus on tasks that humans do best (i.e. human contact). Participatory reviews of the developed prototypes will be completed at each stage (each year) with the LIFE members and clinicians. There are three research questions the investigators hope to answer all while building an effective system to synergistically satisfy the business needs: R1) Although activities of daily living (ADLs) for elder health have previously been documented and categorized, no research has been done to characterize them from the perspective of their feasibility of automation using an affordable mobile manipulation robot. How can known ADLs be characterized according to how much they would benefit from robotic assistance given varying levels of robot capabilities (mobility, limited manipulation, full manipulation)? R2) A manipulator arm must be safe, affordable, and performant enough to assist in ADLs for elder heath. What new breakthroughs are required to develop new manipulation technology that satisfies these constraints? R3) A data-driven service robotics What are the concomitant key usability and acceptance of service features required system has the potential to affect elder health in a positive way. How can predictive service robotics best be used to maintain and improve elder health? Which specific robot behaviors have the most impact on elders' well-being?