Anthropomorphism is a phenomenon that describes the human tendency to see human-like shapes in the environment. It has considerable consequences for people’s choices and beliefs. With the increased presence of robots, it is important to investigate the optimal design for this technology. In this paper we discuss the potential benefits and challenges of building anthropomorphic robots, from both a philosophical perspective and from the viewpoint of empirical research in the fields of human–robot interaction and social psychology. We believe that this broad investigation of anthropomorphism will not only help us to understand the phenomenon better, but can also indicate solutions for facilitating the integration of human-like machines in the real world.

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Anthropomorphism: Opportunities and Challenges in Human-Robot Interaction

In this literature review we explain anthropomorphism and its role in the design of socially interactive robots and human-robot interaction. We illustrate the social phenomenon of anthropomorphism which describes people's tendency to attribute lifelike qualities to objects and other non lifelike artifacts. We present theoretical backgrounds from social sciences, and integrate related work from robotics research, including results from experiments with social robots. We present different approaches for anthropomorphic and humanlike form in a robot's design related to its physical shape, its behavior, and its interaction with humans. This review provides a comprehensive understanding of anthropomorphism in robotics, collects and reports relevant references, and gives an outlook on anthropomorphic human-robot interaction.

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Anthropomorphism and human likeness in the design of robots and human-robot interaction

The experience of interacting with a robot has been shown to be very different in comparison to people's interaction experience with other technologies and artifacts, and often has a strong social or emotional component— a difference that poses potential challenges related to the design and evaluation of HRI. In this paper we explore this difference, and its implications on evaluating HRI. We out- line how this difference is due in part to the general com- plexity of robots' overall context of interaction, related to their dynamic presence in the real world and their tendency to invoke a sense of agency. We suggest that due to these differences HCI evalua- tion methods should be applied to HRI with care, and we present a survey of select HCI evaluation techniques from the perspective of the unique challenges of robots. We pro- pose a view on social interaction with robots that we call the holistic interaction experience, and introduce a set of three perspectives for exploring social interaction with ro- bots: visceral factors of interaction, social mechanics, and social structures. We demonstrate how our three perspec- tives can be used in practice, both as guidelines to discuss and categorize robot interaction, and as a component in the evaluation process. Further, we propose an original heuristic for brainstorming various possibilities of interaction experi- ences based on a concept we call the interaction experience map.

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Evaluating Human-Robot Interaction Focusing on the Holistic Interaction Experience

To interact and cooperate with humans in their daily-life activities, robots should exhibit human-like " intelligence ". This skill will substantially emerge from the interconnection of all the algorithms used to ensure cognitive and interaction capabilities. While new robotics technologies allow us to extend such abilities, their evaluation for social interaction is still challenging. The quality of a human-robot interaction can not be reduced to the evaluation of the employed algorithms: we should integrate the engagement information that naturally arises during interaction in response to the robot's behaviors. In this paper we want to show a practical approach to evaluate the engagement aroused during interactions between humans and social robots. We will introduce a set of metrics useful in direct, face to face scenarios, based on the behaviors analysis of the human partners. We will show how such metrics are useS. M. Anzalone · M. Chetouani Sorbonne Universites , ful to assess how the robot is perceived by humans and how this perception changes according to the behaviors shown by the social robot. We discuss experimental results obtained in two human-interaction studies, with the robots Nao and iCub respectively.

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Evaluating the Engagement with Social Robots

One of robot designers' main goals is to make robots as sociable as possible. Aside from improving robots' actual social functions, a great deal of effort is devoted to making them appear lifelike. This is often achieved by endowing the robot with an anthropomorphic body. However, psychological research on the perception of animacy suggests another crucial factor that might also contribute to attributions of animacy: movement characteristics. In the current study, we investigated how the combination of bodily appearance and movement characteristics of a robot can alter people's attributions of animacy, likability, trustworthiness, and unpleasantness. Participants played games of Tic-Tac-Toe against a robot which (1) either possessed a human form or did not, and (2) either exhibited smooth, lifelike movement or did not. Naturalistic motion was judged to be more animate than mechanical motion, but only when the robot resembled a human form. Naturalistic motion improved likeability regardless of the robot's appearance. Finally, a robot with a human form was rated as more disturbing when it moved naturalistically. Robot designers should be aware that movement characteristics play an important role in promoting robots' apparent animacy. HighlightsMovement characteristics influenced the robot's animacy, likability, and unpleasantness.Baxter was considered to be more likeable when it exhibited naturalistic motion.A full-bodied robot executing mechanistic movement was considered particularly inanimate.A full-bodied robot executing naturalistic movements was particularly unpleasant.

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No fair!! An interaction with a cheating robot