An extended framework for characterizing social robots
1.2 Brief summary of frameworks for characterizing social robots Before outlining the content of our framework, it is useful to first look at existing frameworks for classifying social robots. In particular, existing taxonomies, as such from Fong et al. [70], Yanco et al. [203], Shibata [167], and Dautenhahn [52], are useful to get an understanding of different aspects that may be included in the design space of social robots in HRI research. While this list of frameworks is not exhaustive, we chose these particular ones to base our framework on, as they provide a broad range of classifications and definitions that relates to the scope of this chapter.
As such, Fong et al. [70] contributed a taxonomy of design methods and system components used to build socially interactive robots. These components include robot social capabilities, several design characteristics, and application domains.
Additionally, Yanco et al. [203] provided a framework that included elements of social robot’s design, such as the role that a robot can have when interacting with humans, the types of tasks that robots can perform, different types of robot morphology, and the level of autonomy at which robots can operate.
Similarly, Shibata [167] provided a taxonomy for the function and purpose of social robots by considering different ways of using them for psychological enrichment. Therefore, Shibata classified human-robot interactions in terms of the duration of these interactions and in terms of design characteristics (e.g., robot’s appearance, hardware, and software functionalities), accounting for culture-sensitive aspects.
Moreover, Dautenhahn [52] focused on different evaluation criteria to identify requirements on social skills for robots in different application domains. The author identified four criteria, including contact between the robot and the human (which can vary from no contact or remote contact to repeated long-term contact), the extent of the robot’s functionalities (which can vary from limited to a robot that learns and adapts), the role of the robot (which can vary between machine or tool to assistant, companion, or partner), and the requirement of social skills that a robot needs to have in a given application domain (which can vary from not required/desirable to essential).
With these points in mind, we list below our focuses within each of the 7 dimensions considered.
Appearance—We present a broad classification of robot appearances, synthesizing and going beyond existing ones (Section 2.1).
Social capabilities — We contribute a repositioning of existing classifications aiming to clarify how existing categories related to each other (Section 2.2).
Purpose and application area — We discuss a cross-section of purposes for social robots, and benefiting application areas, with selected examples that include recent developments in the field (Section 2.3).
Relational role—We provide a straightforward and broad classification of the robot’s role in relation to the human(s) (Section 2.4).
Autonomy and intelligence — We clarify the related but distinct concepts of autonomy and intelligence, and discuss their quantification (Section 2.5).
Proximity — We classify interactions according to their spatial features (Section 2.6).
Temporal profile — We look at several time-related aspects of the interaction, namely timespan, duration, and frequency (Section 2.7).
• Communicating using natural language or non-verbal modalities—Examples of these ways of communication are natural speech [200], motion [104, 57] – possibly including gaze [4], gestures or facial expressions –, lights [19, 187], sounds [24], or a combination of them [123]. Mavridis [129] provided a review on verbal and non-verbal interactive communication between humans and robots, defining different types of existing communications such as interaction grounding, affective communications, speech for purpose and planning, among others.
• Expressing affect and/or perceiving human emotions — Beyond Ekamn’s five basic emotions [58] – anger, disgust, fear, happiness, sadness, and surprise –, this may include more complex affective responses such as empathy. For example, Paiva et al. [145] analyzed different ways by which robots and other artificial agents can simulate and trigger empathy in their interactions with humans.
• Exhibiting distinctive personality and character traits—The major components to be considered, according to Robert [153], are human personality when interacting with a robot, robot personality when interacting with humans, dissimilarities or complementary in human-robot personalities, and aspects that facilitate robot personality. Some companies such as Misty Robotics 16 are prioritizing the user personalization of a robot’s personality as an important feature for future commercial social robots.
• Modeling and recognizing social aspects of humans — Modeling human agents allows for robots to interpret aspects of human behavior or communication and appropriately respond to them. Rossi et al. [154] provide a survey of sample works aimed at profiling users according to different types of features. More advanced models may have to consider theory of mind approaches [158].
• Learning and developing new social skills and competencies — In addition to being programmed to have social skills, social robots may have the ability to refine those skills with time through adaptation, or even developing new skills altogether. An active area of research that looks at such paradigms is the area of developmental robotics [125].
• Establishing and maintaining social relationships — Relationships operate over a timespan that goes beyond a few interactions. A number of questions arise when one considers long-term interactions of robots with humans and what it means for a robot to proactively establish and maintain a relationship that is two-sided. Leite et al. [114] established some initial guidelines for the design of social robots for long-term interaction. These include continuity and incremental robot behaviors (e.g., recalling previous activities and self-disclosure), affective interactions and empathy (e.g., displaying contextualized affective reactions), and memory and adaptation (e.g., identifying new and repeated users).