Analyzing children's expectations from robotic companions in educational settings

The use of robots as educational partners has been extensively explored, but less is known about the required characteristics these robots should have to meet children's expectations. Thus the purpose of this study is to analyze children's assumptions regarding morphology, functionality, and body features, among others, that robots should have to interact with them. To do so, we analyzed 142 drawings from 9 to 10 years old children and their answers to a survey provided after interacting with different robotic platforms. The main results convey on a gender-less robot with anthropomorphic (but machine-like) characteristics

Towards Living Machines: current and future trends of tactile sensing, grasping, and social robotics

The development of future technologies can be highly influenced by our deeper understanding of the principles that underlie living organisms. The Living Machines conference aims at presenting (among others) the interdisciplinary work of behaving systems based on such principles. Celebrating the 10 years of the conference, we present the progress and future challenges of some of the key themes presented in the robotics workshop of the Living Machines conference. More specifically, in this perspective paper, we focus on the advances in the field of biomimetics and robotics for the creation of artificial systems that can robustly interact with their environment, ranging from tactile sensing, grasping, and manipulation to the creation of psychologically plausible agents

Children's age influences their use of biological and mechanical questions towards a humanoid

Complex autonomous interactions, biomimetic appearances, and responsive behaviours are increasingly seen in social robots. These features, by design or otherwise, may substantially influence young children’s beliefs of a robot’s animacy. Young children are believed to hold naive theories of animacy, and can miscategorise objects as living agents with intentions; however, this develops with age to a biological understanding. Prior research indicates that children frequently categorise a responsive humanoid as being a hybrid of person and machine; although, with age, children tend towards classifying the humanoid as being more machine-like. Our current research explores this phenomenon, using an unobtrusive method: recording childrens conversational interaction with the humanoid and classifying indications of animacy beliefs in childrens questions asked. Our results indicate that established findings are not an artefact of prior research methods: young children tend to converse with the humanoid as if it is more animate than older children do

Towards a synthetic tutor assistant: The EASEL project and its architecture

Robots are gradually but steadily being introduced in our daily lives. A paramount application is that of education, where robots can assume the role of a tutor, a peer or simply a tool to help learners in a specific knowledge domain. Such endeavor posits specific challenges: affective social behavior, proper modelling of the learner’s progress, discrimination of the learner’s utterances, expressions and mental states, which, in turn, require an integrated architecture combining perception, cognition and action. In this paper we present an attempt to improve the current state of robots in the educational domain by introducing the EASEL EU project. Specifically, we introduce the EASEL’s unified robot architecture, an innovative Synthetic Tutor Assistant (STA) whose goal is to interactively guide learners in a science-based learning paradigm, allowing us to achieve such rich multimodal interactions

You made him be alive: Children’s perceptions of animacy in a humanoid robot

Social robots are becoming more sophisticated; in many cases they offer complex, autonomous interactions, responsive behaviors, and biomimetic appearances. These features may have significant impact on how people perceive and engage with robots; young children may be particularly influenced due to their developing ideas of agency. Young children are considered to hold naive beliefs of animacy and a tendency to mis-categorise moving objects as being alive but, with development, children can demonstrate a biological understanding of animacy. We experimentally explore the impact of children’s age and a humanoid’s movement on children’s perceptions of its animacy. Our humanoid’s behavior varied in apparent autonomy, from motionless, to manually operated, to covertly operated. Across conditions, younger children rated the robot as being significantly more person-like than older children did. We further found an interaction effect: younger children classified the robot as significantly more machine-like if they observed direct operation in contrast observing the motionless or apparently autonomous robot. Our findings replicate field results, supporting the modal model of the developmental trajectory for children’s understanding of animacy. We outline a program of research to both deepen the theoretical understanding of children’s animacy beliefs and develop robotic characters appropriate across key stages of child development

From models of cognition to robot control and back using spiking neural networks

With the recent advent of neuromorphic hardware there has been a corresponding rise in interest in spiking neural network models for the control of real-world artificial agents such as robots. Although models of cognitive mechanisms instantiated in spiking neural networks are nothing new, very few of them are translated onto real robot platforms. In this paper, we attempt such a translation: we implement an existing, biologically plausible model of reaching (the REACH model) demonstrated in 2D simulation on a UR5e robot arm. We are interested in particular in how well such a translation works since this has implications for similar exercises with a vast library of existing models of cognition. In this particular case, after extensions to operations in 3D and for the particular hardware used, we do find that the model is able to learn on the real platform as it did in the original simulation, albeit without reaching the same levels of performance

You made him be alive: Children’s perceptions of animacy in a humanoid robot

Social robots are becoming more sophisticated; in many cases they offer complex, autonomous interactions, responsive behaviors, and biomimetic appearances. These features may have significant impact on how people perceive and engage with robots; young children may be particularly influenced due to their developing ideas of agency. Young children are considered to hold naive beliefs of animacy and a tendency to mis-categorise moving objects as being alive but, with development, children can demonstrate a biological understanding of animacy. We experimentally explore the impact of children’s age and a humanoid’s movement on children’s perceptions of its animacy. Our humanoid’s behavior varied in apparent autonomy, from motionless, to manually operated, to covertly operated. Across conditions, younger children rated the robot as being significantly more person-like than older children did. We further found an interaction effect: younger children classified the robot as significantly more machine-like if they observed direct operation in contrast observing the motionless or apparently autonomous robot. Our findings replicate field results, supporting the modal model of the developmental trajectory for children’s understanding of animacy. We outline a program of research to both deepen the theoretical understanding of children’s animacy beliefs and develop robotic characters appropriate across key stages of child development