Cobot and Sobot: For a new Ontology of Collaborative and Social Robots

Cusano, Nicoletta

doi:10.1007/s10699-022-09860-2

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…However, things are more complex than what can be expected, because these teams not only face completely new scenarios but are tasked with teaching the machine a model of human beings that is not fixed and unchanging but gradually modified by the same interaction with the machine. The intersubjective relationship between humans and social robots has changed and is changing the human as much as the machine: while, on the one hand, the design of the social robot is modeled on the human, on the other hand, interaction with the social robot is changing the human, its sociality, its habits, its acting, and its very way of thinking [ 192 ]. In this way, the human that neuroscience and philosophy are called upon to describe today is a “mobile,” dynamic human, with a “fluid” physiognomy, and this dynamism and continuous transformation depend precisely on the proximity with the machine, which has changed rhythms and times, values, and habits of man.…”

Section: Discussionmentioning

confidence: 99%

Application of Social Robots in Healthcare: Review on Characteristics, Requirements, Technical Solutions

Ragno,

Borboni,

Vannetti

et al. 2023

Sensors

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Cyber-physical or virtual systems or devices that are capable of autonomously interacting with human or non-human agents in real environments are referred to as social robots. The primary areas of application for biomedical technology are nursing homes, hospitals, and private homes for the purpose of providing assistance to the elderly, people with disabilities, children, and medical personnel. This review examines the current state-of-the-art of social robots used in healthcare applications, with a particular emphasis on the technical characteristics and requirements of these different types of systems. Humanoids robots, companion robots, and telepresence robots are the three primary categories of devices that are identified and discussed in this article. The research looks at commercial applications, as well as scientific literature (according to the Scopus Elsevier database), patent analysis (using the Espacenet search engine), and more (searched with Google search engine). A variety of devices are enumerated and categorized, and then our discussion and organization of their respective specifications takes place.

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Section: Discussionmentioning

confidence: 99%

Application of Social Robots in Healthcare: Review on Characteristics, Requirements, Technical Solutions

Ragno,

Borboni,

Vannetti

et al. 2023

Sensors

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“…These social robots or 'so-bots' can fall in line with the social behaviours of humans and make decisions autonomously. Typically, cobots and so-bots are separated but as collaboration has social elements, they are closely related typologies (Cusano, 2022). So-bots can be used for health care and therapy, work and in the public, education, or at home.…”

Section: Industrial Collaborative and Social Robotsmentioning

confidence: 99%

The aesthetics of robot design: towards a classification of morphologies

Mobed,

Wodehouse,

Maier

2024

Proc. Des. Soc.

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Robots are becoming increasingly prevalent in the workplace. As Industry 5.0 pursues human-centric technologies, a greater understanding of what effects aesthetics has on those interacting with robots is needed. This paper sets out robot morphology as a way to characterise key form types, and proposes seven classifications: anthropomorphism, zoomorphism, phytomorphism, artemorphism, functiomorphism, amorphism, and neomorphism. Through an assessment of the current robot aesthetic landscape, design dimensions are identified with examples that can inform future robot design.

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“…This evolutionary phenomenon serves to shorten the reaction time to danger and protect the entire society and all of its members. As a result, the approach proposed in this paper tends to facilitate the transition from a collaborative to a social dimension, even for current collaborative robots that become sobots [103]. Following the perception of the fear signal, the robot implements a strategy to contain the danger by moving to a safe position; this behavior should be recognized by human subjects as a nonverbal message of danger, allowing for a rapid transmission of fear from the robot to the human subjects.…”

Section: Introductionmentioning

confidence: 99%

EEG-Based Empathic Safe Cobot

2022

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An empathic collaborative robot (cobot) was realized through the transmission of fear from a human agent to a robot agent. Such empathy was induced through an electroencephalographic (EEG) sensor worn by the human agent, thus realizing an empathic safe brain-computer interface (BCI). The empathic safe cobot reacts to the fear and in turn transmits it to the human agent, forming a social circle of empathy and safety. A first randomized, controlled experiment involved two groups of 50 healthy subjects (100 total subjects) to measure the EEG signal in the presence or absence of a frightening event. The second randomized, controlled experiment on two groups of 50 different healthy subjects (100 total subjects) exposed the subjects to comfortable and uncomfortable movements of a collaborative robot (cobot) while the subjects’ EEG signal was acquired. The result was that a spike in the subject’s EEG signal was observed in the presence of uncomfortable movement. The questionnaires were distributed to the subjects, and confirmed the results of the EEG signal measurement. In a controlled laboratory setting, all experiments were found to be statistically significant. In the first experiment, the peak EEG signal measured just after the activating event was greater than the resting EEG signal (p < 10−3). In the second experiment, the peak EEG signal measured just after the uncomfortable movement of the cobot was greater than the EEG signal measured under conditions of comfortable movement of the cobot (p < 10−3). In conclusion, within the isolated and constrained experimental environment, the results were satisfactory.

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Cobot and Sobot: For a new Ontology of Collaborative and Social Robots

Cited by 8 publications

References 21 publications

Application of Social Robots in Healthcare: Review on Characteristics, Requirements, Technical Solutions

Application of Social Robots in Healthcare: Review on Characteristics, Requirements, Technical Solutions

The aesthetics of robot design: towards a classification of morphologies

EEG-Based Empathic Safe Cobot

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