How Can a Robot Signal Its Incapability to Perform a Certain Task to Humans in an Acceptable Manner?

In this paper, a robot that is using politeness to overcome its incapability to serve is presented. The mobile robot “Alex” is interacting with human office colleagues in their environment and delivers messages, phone calls, and companionship. The robot's battery capacity is not sufficient to survive a full working day. Thus, the robot needs to recharge during the day. By doing so it is unavailable for tasks that involve movement. The study presented in this paper supports the idea that an incapability of fullfiling an appointed task can be overcome by politeness and showing appropriate behaviour. The results, reveal that, even the simple adjustment of spoken utterances towards a more polite phrasing can change the human's perception of the robot companion. This change in the perception can be made visible by analysing the human's behaviour towards the robot

Challenges in Collaborative HRI for Remote Robot Teams

Collaboration between human supervisors and remote teams of robots is highly challenging, particularly in high-stakes, distant, hazardous locations, such as off-shore energy platforms. In order for these teams of robots to truly be beneficial, they need to be trusted to operate autonomously, performing tasks such as inspection and emergency response, thus reducing the number of personnel placed in harm's way. As remote robots are generally trusted less than robots in close-proximity, we present a solution to instil trust in the operator through a `mediator robot' that can exhibit social skills, alongside sophisticated visualisation techniques. In this position paper, we present general challenges and then take a closer look at one challenge in particular, discussing an initial study, which investigates the relationship between the level of control the supervisor hands over to the mediator robot and how this affects their trust. We show that the supervisor is more likely to have higher trust overall if their initial experience involves handing over control of the emergency situation to the robotic assistant. We discuss this result, here, as well as other challenges and interaction techniques for human-robot collaboration.Comment: 9 pages. Peer reviewed position paper accepted in the CHI 2019 Workshop: The Challenges of Working on Social Robots that Collaborate with People (SIRCHI2019), ACM CHI Conference on Human Factors in Computing Systems, May 2019, Glasgow, U

A systematic review of attitudes, anxiety, acceptance, and trust towards social robots

As social robots become more common, there is a need to understand how people perceive and interact with such technology. This systematic review seeks to estimate people’s attitudes toward, trust in, anxiety associated with, and acceptance of social robots; as well as factors that are associated with these beliefs. Ninety-seven studies were identified with a combined sample of over 13,000 participants and a standardized score was computed for each in order to represent the valence (positive, negative, or neutral) and magnitude (on a scale from 1 to − 1) of people’s beliefs about robots. Potential moderating factors such as the robots’ domain of application and design, the type of exposure to the robot, and the characteristics of potential users were also investigated. The findings suggest that people generally have positive attitudes towards social robots and are willing to interact with them. This finding may challenge some of the existing doubt surrounding the adoption of robotics in social domains of application but more research is needed to fully understand the factors that influence attitudes

Examining the use of robots as teacher assistants in UAE classrooms : teacher and student perspectives

Aim/Purpose - This study sought to understand the views of both teachers and students on the usage of humanoid robots as teaching assistants in a specifically Arab context. Background - Social robots have in recent times penetrated the educational space. Although prevalent in Asia and some Western regions, the uptake, perception and acceptance of educational robots in the Arab or Emirati region is not known. Methodology - A total of 20 children and 5 teachers were randomly selected to comprise the sample for this study, which was a qualitative exploration executed using focus groups after an NAO robot (pronounced now) was deployed in their school for a day of revision sessions. Contribution - Where other papers on this topic have largely been based in other countries, this paper, to our knowledge, is the first to examine the potential for the integration of educational robots in the Arab context. Findings - The students were generally appreciative of the incorporation of humanoid robots as co-teachers, whereas the teachers were more circumspect, expressing some concerns and noting a desire to better streamline the process of bringing robots to the classroom. Recommendations for Practitioners - We found that the malleability of the robot’s voice played a pivotal role in the acceptability of the robot, and that generally students did well in smaller groups with the robot; teachers expressed concern that the children would become easily distracted should too many children be privy to one robot. Recommendations for Researchers - Our results provide valuable recommendations for researchers in the area. We believe, there needs to be continued efforts in devising suitable methodological assessment tools to evaluate student and teacher attitudes in the classroom particularly in the Arab world. We also advise researchers to focus on providing adaptive behavior in the context of educational robots. There are different distinct areas that need further clarifications and study based on our review. Impact on Society - On a wider scale, the findings of this paper have a huge implication for the educational technology as the integration of robotics in education is one of the emerging trends in the area, particularly in the UAE. This study allows to answer questions related to attitudes and perceptions of both teachers and students toward educational robots in the UAE. Future Research - Possible avenues of research in the area include focusing on the adaptive and natural behavior of robots in disciplines other than Mathematics as a means of successfully integrating robots in the classroom

Examining the use of Robots as Teacher Assistants in Uae Classrooms: Teacher and Student Perspectives

Aim/Purpose This study sought to understand the views of both teachers and students on the usage of humanoid robots as teaching assistants in a specifically Arab context. Background Social robots have in recent times penetrated the educational space. Although prevalent in Asia and some Western regions, the uptake, perception and ac-ceptance of educational robots in the Arab or Emirati region is not known. Methodology A total of 20 children and 5 teachers were randomly selected to comprise the sample for this study, which was a qualitative exploration executed using fo-cus groups after an NAO robot (pronounced now) was deployed in their school for a day of revision sessions. Contribution Where other papers on this topic have largely been based in other countries, this paper, to our knowledge, is the first to examine the potential for the inte-gration of educational robots in the Arab context. Findings The students were generally appreciative of the incorporation of humanoid robots as co-teachers, whereas the teachers were more circumspect, express-ing some concerns and noting a desire to better streamline the process of bringing robots to the classroom. Recommendations for Practitioners We found that the malleability of the robot’s voice played a pivotal role in the acceptability of the robot, and that generally students did well in smaller groups with the robot; teachers expressed concern that the children would become easily distracted should too many children be privy to one robot. Recommendations for Researchers Our results provide valuable recommendations for researchers in the area. We believe, there needs to be continued efforts in devising suitable methodo-logical assessment tools to evaluate student and teacher attitudes in the class-room particularly in the Arab world. We also advise researchers to focus on providing adaptive behavior in the context of educational robots. There are different distinct areas that need further clarifications and study based on our review. Impact on Society On a wider scale, the findings of this paper have a huge implication for the educational technology as the integration of robotics in education is one of the emerging trends in the area, particularly in the UAE. This study allows to answer questions related to attitudes and perceptions of both teachers and students toward educational robots in the UAE. Future Research Possible avenues of research in the area include focusing on the adaptive and natural behavior of robots in disciplines other than Mathematics as a means of successfully integrating robots in the classroom

The impact of peoples' personal dispositions and personalities on their trust of robots in an emergency scenario

Humans should be able to trust that they can safely interact with their home companion robot. However, robots can exhibit occasional mechanical, programming or functional errors. We hypothesise that the severity of the consequences and the timing of a robot's different types of erroneous behaviours during an interaction may have different impacts on users' attitudes towards a domestic robot. First, we investigated human users' perceptions of the severity of various categories of potential errors that are likely to be exhibited by a domestic robot. Second, we used an interactive storyboard to evaluate participants' degree of trust in the robot after it performed tasks either correctly, or with 'small' or 'big' errors. Finally, we analysed the correlation between participants' responses regarding their personality, predisposition to trust other humans, their perceptions of robots, and their interaction with the robot. We conclude that there is correlation between the magnitude of an error performed by a robot and the corresponding loss of trust by the human towards the robot. Moreover we observed that some traits of participants' personalities (conscientiousness and agreeableness) and their disposition of trusting other humans (benevolence) significantly increased their tendency to trust a robot more during an emergency scenario.Peer reviewe

End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification

Autoregressive decoding is the only part of sequence-to-sequence models that prevents them from massive parallelization at inference time. Non-autoregressive models enable the decoder to generate all output symbols independently in parallel. We present a novel non-autoregressive architecture based on connectionist temporal classification and evaluate it on the task of neural machine translation. Unlike other non-autoregressive methods which operate in several steps, our model can be trained end-to-end. We conduct experiments on the WMT English-Romanian and English-German datasets. Our models achieve a significant speedup over the autoregressive models, keeping the translation quality comparable to other non-autoregressive models.Comment: EMNLP 201

A computational model of human-robot spatial interactions based on a qualitative trajectory calculus

In this paper we propose a probabilistic sequential model of Human-Robot Spatial Interaction (HRSI) using a well-established Qualitative Trajectory Calculus (QTC) to encode HRSI between a human and a mobile robot in a meaningful, tractable, and systematic manner. Our key contribution is to utilise QTC as a state descriptor and model HRSI as a probabilistic sequence of such states. Apart from the sole direction of movements of human and robot modelled by QTC, attributes of HRSI like proxemics and velocity profiles play vital roles for the modelling and generation of HRSI behaviour. In this paper, we particularly present how the concept of proxemics can be embedded in QTC to facilitate richer models. To facilitate reasoning on HRSI with qualitative representations, we show how we can combine the representational power of QTC with the concept of proxemics in a concise framework, enriching our probabilistic representation by implicitly modelling distances. We show the appropriateness of our sequential model of QTC by encoding different HRSI behaviours observed in two spatial interaction experiments. We classify these encounters, creating a comparative measurement, showing the representational capabilities of the model