Providing tablets as collaborative task workspace for human-robot interaction

©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 8th ACM/IEEE International Conference on Human-robot Interaction, HRI '13, Tokyo, Japan, March 3-6, 2013.In a recent conference on assistive technology in special education and rehabilitation, over 54 percentage of the sessions were directly or indirectly involved with tablets. Following this trend, many traditional assistive technologies are now transitioning from standalone devices into apps on mobile devices. As such, this paper follows this trend by discussing transforming a tablet into an HRI research platform where our robotic system engages the user in social interaction by learning how to operate a given app (task) using guidance from the user. The objective is to engage the robot within the context of the user's task by understanding the task's underlying rules and structures. An overview of the HRI toolkit is presented and a knowledge-based approach in modeling a task is discussed where previously learned cases are reused to solve a new problem

Understanding the Uncertainty Loop of Human-Robot Interaction

Recently the field of Human-Robot Interaction gained popularity, due to the wide range of possibilities of how robots can support humans during daily tasks. One form of supportive robots are socially assistive robots which are specifically built for communicating with humans, e.g., as service robots or personal companions. As they understand humans through artificial intelligence, these robots will at some point make wrong assumptions about the humans' current state and give an unexpected response. In human-human conversations, unexpected responses happen frequently. However, it is currently unclear how such robots should act if they understand that the human did not expect their response, or even showing the uncertainty of their response in the first place. For this, we explore the different forms of potential uncertainties during human-robot conversations and how humanoids can, through verbal and non-verbal cues, communicate these uncertainties

A framework for using humanoid robots in the school learning environment

With predictions of robotics and efficient machine learning being the building blocks of the Fourth Industrial Revolution, countries need to adopt a long-term strategy to deal with potential challenges of automation and education must be at the center of this long-term strategy. Education must provide students with a grounding in certain skills, such as computational thinking and an understanding of robotics, which are likely to be required in many future roles. Targeting an acknowledged gap in existing humanoid robot research in the school learning environment, we present a multidisciplinary framework that integrates the following four perspectives: technological, pedagogical, efficacy of humanoid robots and a consideration of the ethical implications of using humanoid robots. Further, this paper presents a proposed application, evaluation and a case study of how the framework can be used.publishedVersio

A situation that we had never imagined: Post-Fukushima virtual collaborations for determining robot task metrics

There is no consensus regarding a common set of metrics for robot task complexity in associated human-robot interactions. This paper is an attempt to address this issue by proposing a new metric so that the educational potential when using robots can be further developed. Tasks in which students in Japan and UK interact in a 3D virtual space to collaboratively program robots to navigate mazes have resulted in quantitative data of immersion, circuit task complexity and robot task complexity. The data has subsequently been collated to create a proposed new metric for tasks involving robots, which we have termed task fidelity. The paper proposes that task fidelity is a quantitative measure of a set robot task in relation to a learner's solution. By quantifying task fidelity educators utilising robots in schools and in higher education will be able to provide tasks commensurate with the expected successful outcomes achieved by the learners

Exploring the Design Space of Extra-Linguistic Expression for Robots

In this paper, we explore the new design space of extra-linguistic cues inspired by graphical tropes used in graphic novels and animation to enhance the expressiveness of social robots. To achieve this, we identified a set of cues that can be used to generate expressions, including smoke/steam/fog, water droplets, and bubbles. We prototyped devices that can generate these fluid expressions for a robot and conducted design sessions where eight designers explored the use and utility of the cues in conveying the robot's internal states in various design scenarios. Our analysis of the 22 designs, the associated design justifications, and the interviews with designers revealed patterns in how each cue was used, how they were combined with nonverbal cues, and where the participants drew their inspiration from. These findings informed the design of an integrated module called EmoPack, which can be used to augment the expressive capabilities of any robot platform

Emotion Transfer from Frontline Social Robots to Human Customers During Service Encounters: Testing an Artificial Emotional Contagion Modell

This research examines mood transitions during human-robot interactions (HRI) compared with human-human interactions (HHI) during service encounters. Based on emotional contagion and social identity theory, we argue that emotion transmission within HRI (e.g., between a frontline service robot and a human customer) may occur through the imitation of the robot’s verbal and bodily expressions by the customer and may be stronger for negative than for positive emotions. The customer’s positive attitude and anxiety toward robots will further be examined as contingencies that strengthen or weaken the emotion transition during the HRI. We already identified the five most important emotions during service encounters (critical incident study with 131 frontline employees). The subsequent output behavior was programmed to a Nao robot and validated (ratings from 234 students). In the next step, we attempt to manipulate the emotional expressions of a frontline social robot and a customer within an experimental study