Mutual Shaping in the Design of Socially Assistive Robots: A Case Study on Social Robots for Therapy

Winkle, Katie; Caleb-Solly, Praminda; Turton, Ailie; Bremner, Paul

doi:10.1007/s12369-019-00536-9

Cited by 65 publications

(23 citation statements)

References 39 publications

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“…The literature related to assistive robots universally stresses the importance to include the end-users from the initial stage of the developmental process to improve the fit between the user needs and robot services and thus the acceptability by the market. The co-designing with users, which can have different levels of intensity (from drafting the initial concept together, to asking feedback on a prototype), has proven to enhance the usability and the acceptability of products [31,32]. Interestingly, only few studies focused on the inclusion of formal and informal caregivers, in addition to elderly people, in the development process [30].…”

Section: Introductionmentioning

confidence: 99%

Assistive robots to improve the independent living of older persons: results from a needs study

Fiorini

Mul

Fabbricotti

et al. 2019

Disability and Rehabilitation: Assistive Technology

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Background: More than 70% of elderly people age 80 and older are experiencing problems in personal mobility. Assistive robotics can represent a concrete support providing also a support for caregivers, clinicians and nurses by reducing their burden. Methods: A total of 20 older people and 34 caregivers (formal and informal) were interviewed in Italy and the Netherlands to investigate and prioritize their needs concerning the personal mobility domains and their attitudes towards assistive robots. The data were analysed from a user point of view by means of thematic content analysis by underlying recurrent topics. Results: The results revealed four categories of needs from the perspective of the older individuals: instrumental needs, rehabilitation needs, personal safety and indoor activities of daily life. Additionally, the results underline how personal mobility issues influence different aspects of daily life. Complementarily, three categories of caregiver needs were also distinguished: instrumental needs, rehabilitation monitoring needs and checkup needs. The highest percentage of participants showed a positive expectation towards assistive robotics. Conclusions: The results were clustered according to the robot abilities (i.e., motion, interaction, manipulation, decision support and perception abilities) as a list of functional and technical requirements that should be developed to address all the needs related to the personal mobility. Robotic developer teams that work in this context could take advantage of this research. Additionally, this work can be used as a basis for clinicians and nurses working in geriatric units to understand how the robots can support and enhance their work.The incidence of personal mobility limitations affects 35% of adults age 70 and older and 72% of people over 80 years of age. Assistive robots can support elderly people during daily tasks: they could promote their personal mobility acting as a supporting tool. The results of the needs analysis revealed four categories of needs from the perspective of the older individuals: instrumental needs, rehabilitation needs, personal safety, and indoor activities of daily life. Three categories of caregiver needs were also distinguished: instrumental needs, rehabilitation monitoring needs, and check-up needs.

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Section: Introductionmentioning

confidence: 99%

Assistive robots to improve the independent living of older persons: results from a needs study

Fiorini

Mul

Fabbricotti

et al. 2019

Disability and Rehabilitation: Assistive Technology

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“…This approach facilitates the creation of "more socially robust, responsive, and responsible robots" (Šabanović, 2010). In particular, the mutual shaping structure successfully applied by Winkle et al (2019) was used to structure our three studies. Winkle et al propose to split up mutual shaping sessions in three main parts:…”

Section: Methodsmentioning

confidence: 99%

“…This approach facilitates the creation of “more socially robust, responsive, and responsible robots” (Šabanović, 2010 ). In particular, the mutual shaping structure successfully applied by Winkle et al ( 2019 ) was used to structure our three studies. Winkle et al propose to split up mutual shaping sessions in three main parts: Pre-demonstration Discussion to understand participants' initial ideas on the topic before being given information, Project Presentation and Robot Demonstrations to introduce participants to the topic of the session by giving an overview of the state of the art, aims of the project, an explanation of the topic, and (perhaps) a robot demonstration, and Post-demonstration Discussion for participants to give their opinions to researchers about the topic as well as their requirements to advance in the development of the particular technology in discussion.…”

Section: Methodsmentioning

confidence: 99%

Mutual Shaping in Swarm Robotics: User Studies in Fire and Rescue, Storage Organization, and Bridge Inspection

et al. 2020

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Many real-world applications have been suggested in the swarm robotics literature. However, there is a general lack of understanding of what needs to be done for robot swarms to be useful and trusted by users in reality. This paper aims to investigate user perception of robot swarms in the workplace, and inform design principles for the deployment of future swarms in real-world applications. Three qualitative studies with a total of 37 participants were done across three sectors: fire and rescue, storage organization, and bridge inspection. Each study examined the users' perceptions using focus groups and interviews. In this paper, we describe our findings regarding: the current processes and tools used in these professions and their main challenges; attitudes toward robot swarms assisting them; and the requirements that would encourage them to use robot swarms. We found that there was a generally positive reaction to robot swarms for information gathering and automation of simple processes. Furthermore, a human in the loop is preferred when it comes to decision making. Recommendations to increase trust and acceptance are related to transparency, accountability, safety, reliability, ease of maintenance, and ease of use. Finally, we found that mutual shaping, a methodology to create a bidirectional relationship between users and technology developers to incorporate societal choices in all stages of research and development, is a valid approach to increase knowledge and acceptance of swarm robotics. This paper contributes to the creation of such a culture of mutual shaping between researchers and users, toward increasing the chances of a successful deployment of robot swarms in the physical realm.

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“…Moreover, with the advancement in OPO design and technology, and progress made in the area of robotics and artificial intelligence (AI), we are fast moving beyond work simplification to what we will call ‘work complication’. For example, robots already have the capability to work in service and entertainment roles, as well as assistive technology, rehabilitation, surgery and therapy (Asprino et al, 2019; Winkle et al, 2019). AI-equipped robots are partly autonomous and carry out their missions in the immediate shared environment and frequently interact with humans.…”

Section: The Opo: What the Future Holdsmentioning

confidence: 99%

The physical environment of office work: Future open plan offices

Ayoko

Ashkanasy

2020

Australian Journal of Management

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Different configurations of the physical environment of office work are rapidly changing the way office workers behave and perform at work. In particular, organisations today are progressively accommodating their employees in open plan offices (OPOs). In this article, we focus on the OPO and discuss its future and implications for research and practice. Specifically, we build on recent advances in the field to propose that new OPO configurations will require new forms of work behaviour involving new processes and practices, and new research approaches. In addition, we discuss possible areas of work that OPO environments of the future might affect; for example, work design, interpersonal processes, noise and distractions, human resource management (HRM) practices and leadership. Along these lines, we suggest future research directions and make recommendations to navigate the intersection of organisational behaviour (OB) and OPO research and practice. JEL Classification: M19

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Mutual Shaping in the Design of Socially Assistive Robots: A Case Study on Social Robots for Therapy

Cited by 65 publications

References 39 publications

Assistive robots to improve the independent living of older persons: results from a needs study

Assistive robots to improve the independent living of older persons: results from a needs study

Mutual Shaping in Swarm Robotics: User Studies in Fire and Rescue, Storage Organization, and Bridge Inspection

The physical environment of office work: Future open plan offices

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