Maximizing the Benefits of Participatory Design for Human-Robot Interaction Research With Older Adults

Immersive participatory design of assistive robots to support older adults

Assistive robots have the potential to support independence, enhance safety, and lower healthcare costs for older adults, as well as alleviate the demands of their care partners. However, ensuring that these robots will effectively and reliably address end-user needs in the long term requires user-specific design factors to be considered during the robot development process. To identify these design factors, we embedded Stretch, a mobile manipulator created by Hello Robot Inc., in the home of an older adult with motor impairments and his care partner for four weeks to support them with everyday activities. An occupational therapist and a robotics engineer lived with them during this period, employing an immersive participatory design approach to co-design and customise the robot with them. We highlight the benefits of this immersive participatory design experience and provide insights into robot design that can be applied broadly to other assistive technologies.

Robotic Vision for Human-Robot Interaction and Collaboration: A Survey and Systematic Review

Robotic vision for human-robot interaction and collaboration is a critical process for robots to collect and interpret detailed information related to human actions, goals, and preferences, enabling robots to provide more useful services to people. This survey and systematic review presents a comprehensive analysis on robotic vision in human-robot interaction and collaboration over the last 10 years. From a detailed search of 3850 articles, systematic extraction and evaluation was used to identify and explore 310 papers in depth. These papers described robots with some level of autonomy using robotic vision for locomotion, manipulation and/or visual communication to collaborate or interact with people. This paper provides an in-depth analysis of current trends, common domains, methods and procedures, technical processes, data sets and models, experimental testing, sample populations, performance metrics and future challenges. This manuscript found that robotic vision was often used in action and gesture recognition, robot movement in human spaces, object handover and collaborative actions, social communication and learning from demonstration. Few high-impact and novel techniques from the computer vision field had been translated into human-robot interaction and collaboration. Overall, notable advancements have been made on how to develop and deploy robots to assist people.

Socially Assistive Robots for Parkinson's Disease: Needs, Attitudes and Specific Applications as Identified by Healthcare Professionals

To explore how socially assistive robots (SARs) may assist the specific needs of individuals with Parkinson's disease (IwPD), we conducted three focus groups with 12 clinicians who treat IwPD. We present a thematic analysis of their perceptions of the needs of the patients, and their own expectations, perceived advantages, disadvantages and concerns regarding the use of SARs for IwPD. Clinicians were positive towards using SARs for IwPD, if used in the patient's home, for motor, communication, emotional, and cognitive needs, especially for practice and for help with activities of daily living. They were concerned that a SAR might be used to replace clinicians’ work, and stressed it should only augment the clinicians’ work. They thought a SAR may relieve some of the burden experienced by informal caregivers, and identified specific applications for SARs for PD. We asked 18 stakeholders (nine IwPD, nine family members) to rate their level of agreement with the clinicians’ statements. The greatest divergence between their views and those of the clinicians was on the topic of using a SAR as a companion, or as a feeding assistant, to which they objected. This work may be used as a basis for future studies designing SARs for IwPD.

Crisis Ahead? Why Human-Robot Interaction User Studies May Have Replicability Problems and Directions for Improvement

There is a confidence crisis in many scientific disciplines, in particular disciplines researching human behavior, as many effects of original experiments have not been replicated successfully in large-scale replication studies. While human-robot interaction (HRI) is an interdisciplinary research field, the study of human behavior, cognition and emotion in HRI plays also a vital part. Are HRI user studies facing the same problems as other fields and if so, what can be done to overcome them? In this article, we first give a short overview of the replicability crisis in behavioral sciences and its causes. In a second step, we estimate the replicability of HRI user studies mainly 1) by structural comparison of HRI research processes and practices with those of other disciplines with replicability issues, 2) by systematically reviewing meta-analyses of HRI user studies to identify parameters that are known to affect replicability, and 3) by summarizing first replication studies in HRI as direct evidence. Our findings suggest that HRI user studies often exhibit the same problems that caused the replicability crisis in many behavioral sciences, such as small sample sizes, lack of theory, or missing information in reported data. In order to improve the stability of future HRI research, we propose some statistical, methodological and social reforms. This article aims to provide a basis for further discussion and a potential outline for improvements in the field.