Haptic interaction between naive participants and mobile manipulators in the context of healthcare
Chen, Tiffany L.
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Human-scale mobile robots that manipulate objects (mobile manipulators) have the potential to perform a variety of useful roles in healthcare. Many promising roles for robots require physical contact with patients and caregivers, which is fraught with both psychological and physical implications. In this thesis, we used a human factors approach to evaluate system performance and participant responses when potential end users performed a healthcare task involving physical contact with a robot. We performed four human-robot interaction studies with 100 people who were not experts in robotics (naive participants). We show that physical contact between naive participants and human-scale mobile manipulators can be acceptable and effective in a variety of healthcare contexts. In this thesis, we investigated two forms of touch-based (haptic) interaction relevant to healthcare. First, we studied how participants responded to physical contact initiated by an autonomous robotic nurse. On average, people responded favorably to robot-initiated touch when the robot indicated that it was a necessary part of a healthcare task. However, their responses strongly depended on what they thought the robot's intentions were, which suggests that this will be an important consideration for future healthcare robots. Second, we investigated the coordination of whole-body motion between human-scale robots and people by the application of forces to the robot's hands and arms. Nurses found this haptic interaction to be intuitive and preferred it over a standard gamepad interface. They also navigated the robot through a cluttered healthcare environment in less time, with fewer collisions, and with less cognitive load via haptic interaction. Through a study with expert dancers, we demonstrated the feasibility of robots as dance-based exercise partners. The experts rated a robot that used only haptic interaction to be a good follower according to subjective measures of dance quality. We also determined that healthy older adults were accepting of using a robot for partner dance-based exercise. On average, they found the robot easy and enjoyable to use and that it performed a partnered stepping task well. The findings in this work make several impacts on the design of robots in healthcare. We found that the perceived intent of robot-initiated touch significantly influenced people's responses. Thus, we determined that autonomous robots that initiate touch with patients can be acceptable in some contexts. This result highlights the importance of considering the psychological responses of users when designing physical human-robot interactions in addition to considering the mechanics of performing tasks. We found that naive users across three user groups could quickly learn how to effectively use physical interaction to lead a robot during navigation, positioning, and partnered stepping tasks. These consistent results underscore the value of using physical interaction to enable users of varying backgrounds to lead a robot during whole-body motion coordination across different healthcare contexts.