In this paper we introduce the core results of the project on software development for social robotics systems. The usability of maintenance and control features is crucial for many kinds of systems, but in the case of social robotics we also have to take into account that (1) the humanoid robot physically interacts with humans, (2) the conversation with children might have different requirements in comparison to the conversation with adults. The results of our work were implement for the humanoid PAL REEM robot, but their core ideas can be applied for other types of humanoid robots. We developed a web-based solution that supports the management of robot-guided tours, provides recommendations for the users as well as allows for a visual analysis of the data on previous tours.
@cite_26 presented the concept of Social Robot Architecture, which integrates the key elements of agenthood and robotics in a coherent and systematic manner. The ethical and social implications of robotics were discussed by in @cite_25 . @cite_17 examined social-psychology concepts to apply them to the human-robot interaction. @cite_7 presented a case study where they analysed the effects of robot features (human-likeness and gender) and user characteristics on the human-robot interaction acceptance and psychological anthropomorphism. @cite_8 analysed the effects of gesture on the perception of psychological anthropomorphism, by conducting a case study using the Honda humanoid robot. @cite_19 conducted a cross-cultural study on generation of culture dependent facial expressions of humanoid robot. @cite_4 discussed the use of observational studies of human-robot social interaction in open human-inhabited environments. Klein and Cook @cite_20 analysed and compared the findings in the UK and Germany on robot-therapy with emotional robots as a treatment approach for people with cognitive impairments.
@cite_26 @cite_4 @cite_7 @cite_8 @cite_19 @cite_25 @cite_20 @cite_17
2040052159 2157936707 2162104245 2002024051 2118612946 2082173922 2014225072 2097404405
Here, we propose that bidirectionality in implicit motor coordination between humanoid robots and humans could enhance the social competence of human–robot interactions. We first detail some questions pertaining to human–robot interactions, introducing the Uncanny Valley hypothesis. After introducing a framework pertinent for the understanding of natural social interactions, motor resonance, we examine two behaviors derived from this framework: motor coordination, investigated in and informative about human–human interaction, and motor interference, which demonstrate the relevance of the motor resonance framework to describe human perception of humanoid robots. These two lines of investigation are then put together to “close the loop” by proposing to implement a key feature of motor coordination, bidirectionality, in robots’ behavior. Finally, we discuss the feasibility of implementing motor coordination between humanoid robots and humans, and the consequences of this implementation in enhancing the social competence of robots interacting with humans. Keywords: interpersonal interaction, motor resonance, motor coordination, motor interference, social robotics, anthropomorphism As robots enter the everyday physical world of people, it is important that they abide by society's unspoken social rules such as respecting people's personal spaces. In this paper, we explore issues related to human personal space around robots, beginning with a review of the existing literature in human-robot interaction regarding the dimensions of people, robots, and contexts that influence human-robot interactions. We then present several research hypotheses which we tested in a controlled experiment (N=30). Using a 2 (robotics experience vs. none: between-participants) × 2 (robot head oriented toward a participant's face vs. legs: within-participants) mixed design experiment, we explored the factors that influence proxemic behavior around robots in several situations: (1) people approaching a robot, (2) people being approached by an autonomously moving robot, and (3) people being approached by a teleoperated robot. We found that personal experience with pets and robots decreases a person's personal space around robots. In addition, when the robot's head is oriented toward the person's face, it increases the minimum comfortable distance for women, but decreases the minimum comfortable distance for men. We also found that the personality trait of agreeableness decreases personal spaces when people approach robots, while the personality trait of neuroticism and having negative attitudes toward robots increase personal spaces when robots approach people. These results have implications for both human-robot interaction theory and design. Future applications for personal robots motivate research into developing robots that are intelligent in their interactions with people. Toward this goal, in this paper we present an integrated socio-cognitive architecture to endow an anthropomorphic robot with the ability to infer mental states such as beliefs, intents, and desires from the observable behavior of its human partner. The design of our architecture is informed by recent findings from neuroscience and embodies cognition that reveals how living systems leverage their physical and cognitive embodiment through simulation-theoretic mechanisms to infer the mental states of others. We assess the robot's mindreading skills on a suite of benchmark tasks where the robot interacts with a human partner in a cooperative scenario and a learning scenario. In addition, we have conducted human subjects experiments using the same task scenarios to assess human performance on these tasks and to compare the robot's performance with that of people. In the process, our human subject studies also reveal some interesting insights into human behavior. This article presents the results of video-based Human Robot Interaction (HRI) trials which investigated people's perceptions of different robot appearances and associated attention-seeking features and behaviors displayed by robots with different appearance and behaviors. The HRI trials studied the participants' preferences for various features of robot appearance and behavior, as well as their personality attributions towards the robots compared to their own personalities. Overall, participants tended to prefer robots with more human-like appearance and attributes. However, systematic individual differences in the dynamic appearance ratings are not consistent with a universal effect. Introverts and participants with lower emotional stability tended to prefer the mechanical looking appearance to a greater degree than other participants. It is also shown that it is possible to rate individual elements of a particular robot's behavior and then assess the contribution, or otherwise, of that element to the overall perception of the robot by people. Relating participants' dynamic appearance ratings of individual robots to independent static appearance ratings provided evidence that could be taken to support a portion of the left hand side of Mori's theoretically proposed uncanny valley' diagram. Suggestions for future work are outlined. This thesis puts forward a computational framework that can be used by embodied artificial agents (and in particular autonomous robots) for ontogenetic development. The research investigates methods, endowed with which, an embodied agent can develop control structures for increasingly complex and better adapted behaviour, explicitly and incrementally from its history of interaction with its environment. The temporal horizon of an agent is extended so that past experience can be self-organized into a developing structure that can be used to anticipate the future and act appropriately in environments where state information is incomplete, such as a social environment. A formal definition of sensorimotor experience is given, and Crutchfield’s information metric is used as the basis for comparison of experiences. Information metrics are demonstrated to be able to characterize and identify time-extended behaviour. A definition of a metric space of experiences is followed by the introduction of an architecture that combines this with environmental reinforcement as the basis for a system for robot ontogeny. The architecture is demonstrated and tested in various robotic and simulation experiments. This thesis also introduces the early communication game “Peekaboo” as a tool for the study of human-robot interaction and development. The interaction history architecture is then used by two different robots to develop the capability to engage in the peekaboo game. HRI researchers interested in social robots have made large investments in humanoid robots. There is still sparse evidence that peoples' responses to robots differ from their responses to computer agents, suggesting that agent studies might serve to test HRI hypotheses. To help us understand the difference between people's social interactions with an agent and a robot, we experimentally compared people's responses in a health interview with (a) a computer agent projected either on a computer monitor or life-size on a screen, (b) a remote robot projected life-size on a screen, or (c) a collocated robot in the same room. We found a few behavioral and large attitude differences across these conditions. Participants forgot more and disclosed least with the collocated robot, next with the projected remote robot, and then with the agent. They spent more time with the collocated robot and their attitudes were most positive toward that robot. We discuss tradeoffs for HRI research of using collocated robots, remote robots, and computer agents as proxies of robots. The BERT2 social robot, a platform for the exploration of human-robot interaction, is currently being built at the Bristol Robotics Laboratory. This paper describes work on the robot's face, a hybrid face composed of a plastic faceplate and an LCD display, and our implementation of facial expressions on this versatile platform. We report the implementation of two representations of affect space, each of which map the space of potential emotions to specific facial feature parameters and the results of a series of human-robot interaction experiments to characterize the recognizability of the robot's archetypal facial expressions. The tested subjects' recognition of the implemented facial expressions for happy, surprised, and sad was robust (with nearly 100 recognition). Subjects, however, tended to confuse the expressions for disgusted and afraid with other expressions, with correct recognition rates of 21.1 and 52.6 respectively. Future work involves the addition of more realistic eye movements for stronger recognition of certain responses. These results demonstrate that a hybrid face with affect space facial expression implementations can provide emotive conveyance readily recognized by human beings. Social psychology offers a perspective on the acceptance and adoption of technology that is not often considered in technical circles. In this paper, we discuss several adoption-of-technology models with respect to the acceptance of domestic robots: we examine social-psychology literature and apply it directly to human-robot interaction. We raise key points that we feel will be pivotal to how domestic users respond to robots, and provide a set of guidelines that roboticists and designers of robotic interfaces can use to consider and analyze their designs. Ultimately, understanding how users respond to robots and the reasons behind their responses will enable designers to creating domestic robots that are accepted into homes.