The role of social context in human-robot interaction

Xu, Qianli; Ng, Jamie; Cheong, Yian Ling; Tan, Odelia; Wong, Ji Bin; Tay, Tiong Chee; Park, Taezoon

doi:10.1109/seanes.2012.6299594

Cited by 4 publications

(2 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The context of interaction plays a large role in establishing and maintaining perceived safety during HRI. Several studies explored the effect of context in HRI such as the influence of social context on the acceptance of social robots [90] and the influence of context in robot personality preferences [44]. Joosse et al [44] reported that the users' preference for a robot's personality and behaviors depends on the context of the robot's role and task.…”

Section: Context Of Usementioning

confidence: 99%

A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction

Akalın

Kiselev

Kristoffersson

et al. 2023

Int J of Soc Robotics

View full text Add to dashboard Cite

Safety is a fundamental prerequisite that must be addressed before any interaction of robots with humans. Safety has been generally understood and studied as the physical safety of robots in human–robot interaction, whereas how humans perceive these robots has received less attention. Physical safety is a necessary condition for safe human–robot interaction. However, it is not a sufficient condition. A robot that is safe by hardware and software design can still be perceived as unsafe. This article focuses on perceived safety in human–robot interaction. We identified six factors that are closely related to perceived safety based on the literature and the insights obtained from our user studies. The identified factors are the context of robot use, comfort, experience and familiarity with robots, trust, the sense of control over the interaction, and transparent and predictable robot actions. We then made a literature review to identify the robot-related factors that influence perceived safety. Based the literature, we propose a taxonomy which includes human-related and robot-related factors. These factors can help researchers to quantify perceived safety of humans during their interactions with robots. The quantification of perceived safety can yield computational models that would allow mitigating psychological harm.

show abstract

Section: Context Of Usementioning

confidence: 99%

A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction

Akalın

Kiselev

Kristoffersson

et al. 2023

Int J of Soc Robotics

View full text Add to dashboard Cite

show abstract

“…Another study added user needs as a parameter [161]. Others went on to modify the Almere model further whereby the authors followed the concept of product ecology [162].…”

Section: Uses Of Technology Acceptance Modelsmentioning

confidence: 99%

Social Robots, Brain Machine Interfaces and Neuro/Cognitive Enhancers: Three Emerging Science and Technology Products through the Lens of Technology Acceptance Theories, Models and Frameworks

et al. 2013

View full text Add to dashboard Cite

Social robotics, brain machine interfaces and neuro and cognitive enhancement products are three emerging science and technology products with wide-reaching impact for disabled and non-disabled people. Acceptance of ideas and products depend on multiple parameters and many models have been developed to predict product acceptance. We investigated which frequently employed technology acceptance models (consumer theory, innovation diffusion model, theory of reasoned action, theory of planned behaviour, social cognitive theory, self-determination theory, technology of acceptance model, Unified Theory of Acceptance and Use of Technology UTAUT and UTAUT2) are employed in the social robotics, brain machine interfaces and neuro and cognitive enhancement product literature and which of the core measures used in the technology acceptance models are implicit or explicit engaged with in the literature. OPEN ACCESSTechnologies 2013, 1 4

show abstract