Running Robot, Dog vs. Roomba, and BionicCobot

Robots are expected to become ubiquitous in the near future, working alongside and with people in everyday environments to provide various societal benefits. In contrast to this broad ranging social vision for robotics applications, evaluations of robots and studies of human-robot interaction have largely focused on more constrained contexts, largely dyadic and small group interactions in laboratories. As a result, we have a limited understanding of how robots are perceived, adopted and supported in open-ended, natural social circumstances in which researchers have little control of the ensuing interactions.

This talk will discuss insights from a series of studies of the design and use of socially assistive robots (SARs) for eldercare aimed at expanding our awareness of the broader cultural, organizational, and societal dynamics that affect the use and consequences of robots outside the laboratory. Our in-home interviews with older adults suggested that existing robot designs reproduce unwanted stereotypes of aging, while naturalistic observation of robot use in a nursing home shows that ongoing labor by various groups of users is needed to produce successful voluntary human-robot interactions. In response to these findings, we are currently engaging in participatory design of robots with older adults and clinicians to provide an opportunity for mutual learning, inspire both sides to think beyond common stereotypes of older adults and robots, and identify non-technical issues of particular concern to clinicians and older adults that may affect long-term robot adoption. These concerns include the fit of robots to the home environments and values of older adults, to the labor practices and clinical needs of care staff, and to the broader healthcare infrastructure (e.g. insurance mechanisms). In conclusion, I will discuss ways to address broader organizational and societal issues in the course of robot design and development, working together with potential users and other stakeholders to avoid unwanted consequences and create robust social supports that can cope with the inevitable challenges that emerge when we apply robots in society.

Robots manipulate with super-human speed and dexterity on factory floors. But yet they fail even under moderate amounts of clutter or uncertainty. However, human teleoperators perform remarkable acts of manipulation with the same hardware. My research goal is to bridge the gap between what robotic manipulators can do now and what they are capable of doing. What human operators intuitively possess that robots lack are models of interaction between the manipulator and the world that go beyond pick-and-place. I will describe our work on nonprehensile physics-based manipulation that has produced simple but effective models, integrated with proprioception and perception, that has enabled robots to fearlessly push, pull, and slide objects, and reconfigure clutter that comes in the way of their primary task. But human environments are also filled with humans. Collaborative manipulation is a dance, demanding the sharing of intentions, inferences, and forces between the robot and the human. I will also describe our work on the mathematics of human-robot interaction that has produced a framework for collaboration using Bayesian inference to model the human collaborator, and trajectory optimization to generate fluent collaborative plans. Finally, I will talk about our new initiative on assitive care that focuses on marrying physics, human-robot collaboration, control theory, and rehabilitation engineering to build and deploy caregiving systems.

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