Why Would I Use This in My Home? A Model of Domestic Social Robot Acceptance

Many independent studies in social robotics and human–robot interaction have gained knowledge on various factors that affect people’s perceptions of and behaviors toward robots. However, only a few of those studies aimed to develop models of social robot acceptance integrating a wider range of such factors. With the rise of robotic technologies for everyday environments, such comprehensive research on relevant acceptance factors is increasingly necessary. This article presents a conceptual model of social robot acceptance with a strong theoretical base, which has been tested among the general Dutch population (n = 1,168) using structural equation modeling. The results show a strong role of normative believes that both directly and indirectly affect the anticipated acceptance of social robots for domestic purposes. Moreover, the data show that, at least at this stage of diffusion within society, people seem somewhat reluctant to accept social behaviors from robots. The current findings of our study and their implications serve to push the field of acceptable social robotics forward. For the societal acceptance of social robots, it is vital to include the opinions of future users at an early stage of development. This way future designs can be better adapted to the preferences of potential users.     

Development and validation of a technology acceptance model for safety-enhancing,wearable locating systems

Events of disasters on passenger ships can never be completely excluded while numbers of passengers on cruises are continuously increasing. Innovations in ubiquitous and networked computing such as wearable locating systems for passengers could enable faster muster and more efficient search for missing people. As the safety enhancement depends on the effective usage of these technologies, passengers’ acceptance is crucial, though largely unknown, and infrastructure implies high costs for shipping companies. In order to investigate passengers’ acceptance, a context-specific technology acceptance model was developed based on a literature review and qualitative interviews with passengers. The model was validated by an online survey with 2086 passengers aged between 16 and 81 years. The context-specific factors social influence, expected usefulness, trust, privacy concern, and perceived security risk explain 95% of the variance in the target variable intention to use locating systems with social influence as the strongest predictor. The context-specific factors are most determined by the passenger characteristics age and need for safety. In conclusion, the model presents insights into the relationships between passenger characteristics and context-specific factors enabling systematic interventions to increase acceptance for locating systems and, thereby, contributes to enhance safety for the occurrence of an evacuation.     

Human Robot Engagement and Acceptability in Residential Aged Care

ABSTRACT

People with dementia often suffer the limitation in their ability to communicate and express themselves clearly, consequently spend most of their time alone, and are not engaged in social activity as before. The prolonged lack of engagement has contributed to a variety of negative health effects. The research on engagement and acceptability of people with dementia using assistive technology such as social robots can be useful to provide potential solutions and sustainability. Thus, this article focuses on the service design and the effectiveness of the engagement and acceptability while interacting with a social robot named Matilda being trialed from 2010 until 2013 with 115 participants in Australian residential aged care facilities. Combining the most updated engagement assessment method and the robot acceptance model as the methodology, the findings of this study indicate there is a statistically significant improvement in emotional, visual, and behavioral engagement of older people with social robots over the years. The post-trial survey has also verified their acceptance in the interaction with social robots.     

Correction to: Investigating socially assistive systems from system design and evaluation: a systematic review

Purpose The development of assistive technologies that support people in social interactions has attracted increased attention in HCI. This paper presents a systematic review of studies of Socially Assistive Systems targeted at older adults and people with disabilities. The purpose is threefold: (1) Characterizing related assistive systems with a special focus on the system design, primarily including HCI technologies used and user-involvement approach taken; (2) Examining their ways of system evaluation; (3) Reflecting on insights for future design research. Methods A systematic literature search was conducted using the keywords “social interactions” and “assistive technologies” within the following databases: Scopus, Web of Science, ACM, Science Direct, PubMed, and IEEE Xplore. Results Sixty-five papers met the inclusion criteria and were further analyzed. Our results showed that there were 11 types of HCI technologies that supported social interactions for target users. The most common was cognitive and meaning understanding technologies, often applied with wearable devices for compensating users’ sensory loss; 33.85% of studies involved end-users and stakeholders in the design phase; Four types of evaluation methods were identified. The majority of studies adopted laboratory experiments to measure user-system interaction and system validation. Proxy users were used in system evaluation, especially in initial experiments; 42.46% of evaluations were conducted in field settings, primarily including the participants’ own homes and institutions. Conclusion We contribute an overview of Socially Assistive Systems that support social interactions for older adults and people with disabilities, as well as illustrate emerging technologies and research opportunities for future work.

     

Service robots: System design for tracking people through data fusion and initiating interaction with the human group by inferring social situations

In a situation where a robot initiates conversation with a group of people, questions such as “where is the people group?” and “whether the robot should approach them?” should be addressed. This paper develops a new system that enables a robot to determine whether or not it should approach the aforementioned human group and interact with them after identifying what the current social situation is. The system is mainly to fuse depth-related data to track the positions of a group of people, extract social cues of those people by using depth-related data and a decision network (DN) model, and the main challenge lies in understanding the social cues of the group and the current underlying social situation concerning the relation between the robot and the group. The social cues are based on Proxemics and F-formations, whereas the social situations are categorized as individual-to-individual, individual-to-robot, robot-to-individual, group-to-robot, robot-to-group, confidential discussion and group discussion. Our system proceeds as follows : once a group of people are detected and the social cues of that target group of people are extracted, the corresponding social situation is appropriately inferred, and in turn the robot decides whether it should initiate conversation with the group based on rules to be specified later. The conducted experimental results demonstrate the properness of the system design and the efficacy of the proposed method in recognizing the social cues among individuals of the group as well as the nature of the social situations concerning the group and the robot.     

Human factors and qualitative pedagogical evaluation of a mobile augmented reality system for science education used by learners with physical disabilities

Technology-enhanced learning, employing novel forms of content representation and education service delivery by enhancing the visual perception of the real environment of the user, is favoured by proponents of educational inclusion for learners with physical disabilities. Such an augmented reality computer-mediated learning system has been developed as part of an EU funded research project, namely the CONNECT project. The CONNECT project brings together schools and science centres, and produces novel information and communication technologies based on augmented reality (AR) and web-based streaming and communication, in order to support learning in a variety of settings. The CONNECT AR interactive learning environment can assist users to better contextualize and reinforce their learning in school and in other settings where people learn (i.e. science centres and home). The CONNECT concept and associated technologies encourage users to visit science centres and perform experiments that are not possible in school. They can also build on these experiences back at school and at home with visual augmentations that they are communicated through web-based streaming technology. This paper particularly focuses on a user-centred evaluation approach of human factors and pedagogical aspects of the CONNECT system, as applied to a special needs user group. The main focus of the paper is on highlighting the human factors issues and challenges, in terms of wearability and technology acceptance, while elaborating on some qualitative aspects of the pedagogical effectiveness of the instructional medium that AR technology offers for this group of learners.

Merging social computing with content: a proposal of a new film platform,Avids

ABSTRACT

Film consumers are continuously online and active in various social platforms. This phenomenon has led over-the-top (OTT) providers – empowered by social computing technologies – to establish a social media presence and incorporate elements drawn from social media into their services. However, little is known about existing OTT interfaces and their key social features. This study sought to provide a structured categorisation of the most salient social media features of the best-known applications in the OTT video business. In addition, a new social content network model, Avids, was proposed to connect individuals socially through films. Avids reaches beyond more fixed, functionality-based approaches applied in the development of OTT video sites and focuses on components related to sociality. This approach ensures a unified system in which the overall social media setting is embedded in every functional area of the platform’s architecture, thereby allowing applications to trigger and support social behaviours absent from traditional OTT providers. A purpose-built international online survey was administered to 479 film lovers to assess how Avids’ main features compare with traditional OTT video providers. The questionnaire was based on the technology acceptance model. The results confirm the critical role of sociality in film viewing-related activities.     

Sharing a life with Harvey: Exploring the acceptance of and relationship-building with a social robot

Social robots will become ubiquitous in our everyday environments. These robots could potentially extend life expectancy, and improve the health and quality of life of an aging population. A long-term explorative study has been conducted by installing a social robot for health promotion in elderly people’s own homes. Content analysis of interviews provided an in-depth understanding of the factors that influence the acceptance of and relationship-building with social robots in domestic environments. The permanent presence of a robot in users’ own homes yields the vital challenges social robots encounter to be successfully accepted by their users. These vital acceptance challenges are unlikely to be revealed in one-day laboratory human-robot interaction studies or even in multiple observations of short interactions between humans and robots.     

Development of the multi-functional indoor service robot PSR systems

This paper discusses the development of the multi-functional indoor service robot PSR (Public Service Robots) systems. We have built three versions of PSR systems, which are the mobile manipulator PSR-1 and PSR-2, and the guide robot Jinny. The PSR robots successfully accomplished four target service tasks including a delivery, a patrol, a guide, and a floor cleaning task. These applications were defined from our investigation on service requirements of various indoor public environments. This paper shows how mobile-manipulator typed service robots were developed towards intelligent agents in a real environment. We identified system integration, multi-functionality, and autonomy considering environmental uncertainties as key research issues. Our research focused on solving these issues, and the solutions can be considered as the distinct features of our systems. Several key technologies were developed to satisfy technological consistency through the proposed integration scheme. Woojin Chung was born in Seoul, Korea, in 1970. He received the B.S. at the department of mechanical design and production engineering, Seoul National University in 1993. He received the M.S. degree in 1995 and Ph.D degree in 1998 at the department of Mechano-Informatics, the University of Tokyo. He was a senior research scientist at the Korea Institute of Science and Technology from 1998 to 2005. He joined the department of mechanical engineering, Korea University in 2005 as an assistant professor. He received an excellent paper award from the Robotics Society of Japan in 1996 and a best transactions paper award from the IEEE robotics and automation society in 2002. His research interests include the design and control of nonholonomic underactuated mechanical systems, trailer system design and control, mobile robot navigation, a dexterous robot hand and a system integration of intelligent robots. He is a member of the IEEE, the robotics society of Japan, the institute of control, automation and systems engineers and the Korea robotics society. Gunhee Kim received the B.S. and M.S. degrees at the department of mechanical engineering, Korea Advanced Institute of Science and Technology (KAIST), Korea, in 1999 and 2001, respectively. He was a research scientist in Intelligent Robotics Research Center, at Korea Institute of Science and Technology (KIST), Korea, from 2001 to 2006. Currently, he is a graduate student in the Robotics Institute, Carnegie Mellon University. His research interests include computer vision, artificial intelligence, mobile robot navigation, and discrete event systems. He is a member of the IEEE. Munsang Kim received the B.S. and M.S degree in Mechanical Engineering from the Seoul National University in 1980 and 1982 respectively and the Dr.-Ing. degree in Robotics from the Technical University of Berlin, Germany in 1987. Since 1987 he has been working as a research scientist at Korea Institute of Science and Technology. He has led the Intelligent Robotics Research Center since 2000 and became the director of the “Intelligent Robot—The Frontier 21 Program” since Oct. 2003. His current research interests are design and control of novel mobile manipulation systems, haptic device design and control, and sensor application to intelligent robots.     

Socially Distributed Perception: GRACE plays social tag at AAAI 2005

This paper presents a robot search task (social tag) that uses social interaction, in the form of asking for help, as an integral component of task completion. Socially distributed perception is defined as a robot's ability to augment its limited sensory capacities through social interaction. We describe the task of social tag and its implementation on the robot GRACE for the AAAI 2005 Mobile Robot Competition & Exhibition. We then discuss our observations and analyses of GRACE's performance as a situated interaction with conference participants. Our results suggest we were successful in promoting a form of social interaction that allowed people to help the robot achieve its goal. Furthermore, we found that different social uses of the physical space had an effect on the nature of the interaction. Finally, we discuss the implications of this design approach for effective and compelling human-robot interaction, considering its relationship to concepts such as dependency, mixed initiative, and socially distributed cognition. An erratum to this article can be found at

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Do I have to learn something new? Mental models and the acceptance of replacement technologies

Few studies in technology acceptance have explicitly addressed the acceptance of replacement technologies, technologies that replace legacy ones that have been in use. This article explores this issue through the theoretical lens of mental models. We contend that accepting replacement technologies entails both mental model maintenance and mental model building: mental model maintenance enables users to apply their knowledge of the legacy technologies, and mental model building helps users acquire new knowledge and reform their understanding to use replacement technologies. Both processes affect user perceptions about replacement technologies, which in turn affect user intentions to use them. In addition, this study explores how perceived compatibility between replacement and legacy technologies affects both mental model processes. A research model was developed and empirically tested with survey data. The results in general support our arguments. Based on the findings, we offer a few suggestions that can promote user acceptance of replacement technologies.     

Towards an EEG-based brain-computer interface for online robot control

According to New York Times, 5.6 million people in the United States are paralyzed to some degree. Motivated by requirements of these paralyzed patients in controlling assisted-devices that support their mobility, we present a novel EEG-based BCI system, which is composed of an Emotive EPOC neuroheadset, a laptop and a Lego Mindstorms NXT robot in this paper. We provide online learning algorithms that consist of k-means clustering and principal component analysis to classify the signals from the headset into corresponding action commands. Moreover, we also discuss how to integrate the Emotiv EPOC headset into the system, and how to integrate the LEGO robot. Finally, we evaluate the proposed online learning algorithms of our BCI system in terms of precision, recall, and the F-measure, and our results show that the algorithms can accurately classify the subjects’ thoughts into corresponding action commands.     

Distributed Apprenticeship in Online Communities

Supporting learning in online communities is an important direction for the future of human–computer interaction as people increasingly leverage social technologies to support professional growth and development. However, few have studied how people leverage the socio-technical affordances of online informal workplace communities to develop professional skills in the absence of dedicated expert guidance. We draw from theories of apprenticeship to introduce an emergent theory of distributed apprenticeship, which outlines how community expectations of transparency and mutual support allow for instruction to be directed by a distributed network of nonexperts. We develop distributed apprenticeship through a qualitative study of crowdfunding entrepreneurs, where novices leverage social interactions with community members to develop a wide range of entrepreneurial skills. We then generalize distributed apprenticeship to other workplace contexts and provide design implications for online communities where people develop professional skills with minimal dedicated formal guidance.     

Creating a conversational context through video blogging: A case study of Geriatric1927

Web-based communication technologies such as YouTube can provide opportunities for social contact, especially between older and younger people, and help address issues of social isolation. Currently our understanding of the dynamics of social interaction within this context (particularly for older people) is limited. Elaborating upon this understanding will make it possible to proactively facilitate and support this form of intergenerational social contact. This study focuses on the experiences of an 80-year-old video blogger (vlogger), Geriatric1927, and a video dialogue that develops between himself and three of his younger viewers on a particular topic. Through a multimodal interactional analysis, we show how vloggers create a conversational context between one another through the YouTube website. In particular we describe how vloggers use different communicative modes to establish eye contact, take turns in conversation, share embodied gestures, share their understandings and negotiate simultaneous audiences. Despite a disconnected and ambiguous sense of the other, YouTube is able to facilitate a conversational context in which common ground is shared and social contact and intergenerational communication can occur.     

The role of information support systems in the joint optimization of work systems

Sociotechnical approach preaches the affinity of the social and the technical organization but divides organizations into social and technical subsystems. Thus, it has failed to anticipate the possibilities of new technologies within the social system. The social subsystem of a modern sociotechnical system does not consist of mere human beings but combines people and the technological artifacts they use. In this article, we discuss one such technology, information support, and how it can be used to expand functional redundancy of a sociotechnical system, even the cognitive redundancy of individual people. However, such technologies have often been applied specifically to limit functional redundancy of the sociotechnical system, that is, to reduce communication, learning, and utilization of human talent. The discussion is based on findings from case studies on multimedia‐based interactive task support systems used in lightweight assembly industry in Finland and in Denmark. The case studies provide both justification to the information support approach and questions to be addressed in the future. For example, why did the introduction of so many interactive task support systems fail? © 2000 John Wiley & Sons, Inc.     

Telenoid android robot as an embodied perceptual social regulation medium engaging natural human–humanoid interaction

The present paper aims to validate our research on human–humanoid interaction (HHI) using the minimalist humanoid robot Telenoid. We conducted the human–robot interaction test with 142 young people who had no prior interaction experience with this robot. The main goal is the analysis of the two social dimensions (“Perception” and “Believability”) useful for increasing the natural behaviour between users and Telenoid. We administered our custom questionnaire to human subjects in association with a well defined experimental setting (“ordinary and goal-guided task”). A thorough analysis of the questionnaires has been carried out and reliability and internal consistency in correlation between the multiple items has been calculated. Our experimental results show that the perceptual behaviour and believability, as implicit social competences, could improve the meaningfulness and the natural-like sense of human–humanoid interaction in everyday life task-driven activities. Telenoid is perceived as an autonomous cooperative agent for a shared environment by human beings.     

Testing the moderating role of need for cognition in smartphone adoption

While numerous studies have identified various cognitive and social factors affecting the adoption of new technologies and innovations, the role of individual differences has not yet received full research attention. In this study, we focused on the need for cognition (NFC; Cacioppo, J.T. and Petty, R.E., 1982. The need for cognition. Journal of Personality and Social Psychology, 42, 116–131) and examined the implications of this personality variable relative to smartphone use. The results based on the survey data (N=411) provided support for our hypotheses that NFC is an important motivational personality construct that distinguishes between adopters and non-adopters of smartphones. We also found that NFC moderates the linkages between instrumental beliefs, social influence factors, and behavioural intentions (BI). Specifically, perceived usefulness had a stronger effect on BI for high-NFC people, whereas perceived ease of use and subjective norms had stronger effects for low-NFC people. The findings reveal possible important variations in technology adoption and the role of NFC in governing these alternative decision-making processes. Implications for theory, product design, as well as for managers are discussed.     

Trajectory prediction and tracking using a multi-behaviour social particle filter

3D motion tracking is a challenging task when both the tracked object and the observer are moving. In this paper, we present a multi-behavioural social force-based particle filter to track a group of moving humans from a moving robot using a limited field-of-view monocular camera. The application is a robotic guide and while moving, the robot often loses visibility of one or more people in the group, who must still be tracked. As an example, due to limited space, when the robot takes a sharp turn to avoid an obstacle or circumvent a corner, the visibility of the people at the rear is lost for some time. Therefore, several human social behavioural aspects have been implemented to predict the human’s motion in a group. The model accounts for attraction and repulsion between the people of the group and those with the robot, to maintain a comfortable social distance with each other at equilibrium. Additionally, when any person leaves the group then the track is deleted and after joining the track is automatically re-initialized. In the literature, the time of invisibility is a criterion to detect a person who has left the system, which however cannot be used here since the invisibility may be due to a limited field of view or the robot making a sharp turn to avoid an obstacle or circumventing a corner. Social heuristics are used to accurately detect people leaving the robotic system. The tracked trajectory is compared with ground truth and our system gives a very less error when compared with several baseline approaches. False positives are reduced, and the accuracy also increased with our proposed model as compared to other baseline methods. This method has been tested on several scenarios to ensure its validity.

     

LEARNING BEHAVIORS BY AN AUTONOMOUS SOCIAL ROBOT WITH MOTIVATIONS

In this study, an autonomous social robot is living in a laboratory where it can interact with several items (people included). Its goal is to learn by itself the proper behaviors in order to maintain its well-being at as high a quality as possible. Several experiments have been conducted to test the performance of the system.

The Object Q-Learning algorithm has been implemented in the robot as the learning algorithm. This algorithm is a variation of the traditional Q-Learning because it considers a reduced state space and collateral effects. The comparison of the performance of both algorithms is shown in the first part of the experiments. Moreover, two mechanisms intended to reduce the learning session durations have been included: Well-Balanced Exploration and Amplified Reward. Their advantages are justified in the results obtained in the second part of the experiments.

Finally, the behaviors learned by our robot are analyzed. The resulting behaviors have not been preprogrammed. In fact, they have been learned by real interaction in the real world and are related to the motivations of the robot. These are natural behaviors in the sense that they can be easily understood by humans observing the robot.