The purpose of this study was to test the effects of robot-to-human information exchanges on the development of human situation awareness under differing levels of visuospatial perspective taking and the effect of situation awareness on the quality of human assistance provided to a robot. Fifty-six male participants with ages ranging from 18 to 29 (M = 18.89, SD = 3.41) were included in the analysis of the results. The results showed that if robots can increasingly support a human's understanding of when assistance is needed, they will be better able to provide that assistance. When spatial information was added to robot-to-human information exchanges, representing that spatial information in global-relative reference frames was more beneficial than representing that information in reference to the human's view of the environment.
Dear colleagues in the HRI community, JHRI needs you! It gives us great pleasure to join the Journal of Human-Robot Interaction (JHRI) as the new Editors-in-Chief. We are truly honored to serve the human-robot interaction (HRI) community in this role, and brimming with excitement for the journal in the coming years.
Over the last few years, technological developments in semi-autonomous machines have raised awareness about the strategic importance of human-robot interaction (HRI) and its technical and social implications.At the same time, HRI still lacks an established pedagogic tradition in the coordination of its intrinsically interdisciplinary nature.This scenario presents steep and urgent challenges for HRI education.Our contribution presents a normative interdisciplinary dialogic framework for HRI education, denoted InDia wheel, aimed toward seamless and coherent integration of the variety of disciplines that contribute to HRI.Our framework deemphasizes technical mastery, reducing it to a necessary yet not sufficient condition for HRI design, thus modifying the stereotypical narration of HRI-relevant disciplines and creating favorable conditions for a more diverse participation of students.Prospectively, we argue, the design of an educational 'space of interaction' that focuses on a variety of voices, without giving supremacy to one over the other, will be key to successful HRI education and practice.
Dear colleagues in the HRI community, I have been given the honor and privilege to write the editorial introduction for this final issue of the Journal of Human-Robot Interaction, before its reemergence as the ACM Transactions on Human-Robot Interaction. It has been a distinct pleasure to serve as the JHRI Managing Editor for the last two and a half years. I am grateful to our founding editors, Sara Kiesler and Mike Goodrich, for giving me this opportunity. Working with our current editors, Chad Jenkins and Selma Sabanovic, we have made great steps to continue advancing the journal and its scholarship. All of us are already working hard to produce an outstanding first issue of ACM THRI!
This article illustrates how HRI can be a useful vehicle for exposing technologist students (e.g., in computer science or engineering) to social aspects of technology and to the concrete benefits that a socially aware perspective can bring to technology design, implementation, and use. The article details the strategy and layout taken with the graduate-level Human-Robot Interaction (HRI) course at the University of Manitoba, Canada, between 2011 and 2015, for the purposes of introducing students to social considerations surrounding technology. Further, this paper reflects on the results from three iterations of the course and demonstrates how students have engaged socially aware thinking and analysis in their course projects. This single, introductory HRI course can be a catalyst for encouraging socially aware thinking in technologist students.
As robots become commonplace, and for successful human-robot interaction to occur, people will need to trust them. Two experiments were conducted using the "minimal group paradigm" to explore whether social identity theory influences trust formation and impressions of a robot. In Experiment 1, participants were allocated to either a "robot" or "computer" group, and then they played a cooperative visual tracking game with an Aldebaran Nao humanoid robot as a partner. We hypothesised participants in the "robot group" would demonstrate intergroup bias by sitting closer to the robot (proxemics) and trusting the robot's suggested answers more frequently than their "computer group" counterparts. Experiment 2 used an almost identical procedure with a different set of participants; however, all participants were assigned to the "robot group" and thee different levels of anthropomorphic robot movement were manipulated. Our results suggest that intergroup bias and humanlike movement can significantly affect human-robot approach behaviour. Significant effects were found for trusting the robot's suggested answers with respect to task difficulty, but not for group membership or robot movement.
Socially assistive robotics (SAR) has increasingly been shown to have potential as a tool for social skills therapy for children with autism, a developmental disorder associated with atypical social development. This work presents the results of a study of robot agency on child-robot interactions involving children with autism. We describe the development of a SAR interaction scenario with both agent-like and object-like robot behaviors and present the results of a pilot study of six children with autism interacting with a humanoid robot with the full controller, as well as three types of control: a non-humanoid "box" robot with similar behavior (reduced morphological agency), a humanoid robot with random behavior (reduced behavioral agency), and a robotic toy (reduced morphological and behavioral agency). We find that the children can be divided into two groups depending on their reaction to the robot; for some children, the robot was an engaging object that elicited social behavior by providing novel and appealing sensory experiences (primarily bubbleblowing), while for other children, the robot was an agent and elicited social behavior through agentlike actions such as autonomous movement. We found that the first group had small differences between robot conditions and vocalized most with the bubble-blowing toy, while the second group vocalized most with the humanoid robots and looked less at the humanoid portion of the robot with reduced behavioral agency.
An important open problem for enabling truly taskable robots is the lack of task-general natural language mechanisms within cognitive robot architectures that enable robots to understand typical forms of human directives and generate appropriate responses. In this paper, we first provide experimental evidence that humans tend to phrase their directives to robots indirectly, especially in socially conventionalized contexts. We then introduce pragmatic and dialogue-based mechanisms to infer intended meanings from such indirect speech acts and demonstrate that these mechanisms can handle all indirect speech acts found in our experiment as well as other common forms of requests.
A reliable wireless connection between the operator and the teleoperated unmanned ground vehicle (UGV) is critical in many urban search and rescue (USAR) missions. Unfortunately, as was seen in, for example, the Fukushima nuclear disaster, the networks available in areas where USAR missions take place are often severely limited in range and coverage. Therefore, during mission execution, the operator needs to keep track of not only the physical parts of the mission, such as navigating through an area or searching for victims, but also the variations in network connectivity across the environment. In this paper, we propose and evaluate a new teleoperation user interface (UI) that includes a way of estimating the direction of arrival (DoA) of the radio signal strength (RSS) and integrating the DoA information in the interface. The evaluation shows that using the interface results in more objects found, and less aborted missions due to connectivity problems, as compared to a standard interface. The proposed interface is an extension to an existing interface centered on the video stream captured by the UGV. But instead of just showing the network signal strength in terms of percent and a set of bars, the additional information of DoA is added in terms of a color bar surrounding the video feed. With this information, the operator knows what movement directions are safe, even when moving in regions close to the connectivity threshold.
Educational robotics has great potential as a learning tool at all levels, from kindergarten to the university. It provides rich opportunities for collaborative knowledge building and skills acquisition through the manipulation of and interaction with robots. Despite the remarkable progress in this field, the scope and impact of robot-based activities have primarily focused on the teaching of technical school subjects (i.e., computer science, mathematics, and physics). This work proposes to support the learning and teaching of non-technical school subjects through drama-based activities with multiple robots. This approach provides a multisensory learning environment where students can learn through representations or simulations of ideas, events, stories, phenomena, or processes using multiple robot actors. Based on the drama process used by teachers, we propose steps to create and perform plays with robot actors in an educational context and discuss different alternatives for its implementation. Finally, we discuss the challenges of creating plays with multiple robots for educational purposes.
A new race of artifacts comes equipped with behavioral properties. Those properties transmute the very nature of the object, granting it a life of its own and a special status that stems from the psychological attributions humans naturally produce when confronted by autonomous movements. This article examines what makes behavioral objects special in terms of the psychological properties they evoke in an observer. We look into the notion of behavior and evaluate to what extent the concept of anthropomorphism is a valid construct when considering the behavior of artificial objects. Based on recent research in cognitive psychology, we propose a framework to conceptualize the way people infer psychological attributes from movement, and the way it applies to behavioral objects.
Experiments were conducted to quantify the direction of robot approach that a pair of seated people find most comfortable. Three maximally-different seating configurations and eight directions of robot approach were considered. The data were analysed using Rayleigh's test of uniformity, a directional statistics method. Results from 140 participants showed robot approach directions that minimise participant discomfort align spatially with regions that allow good sight of the robot by both people and are centred on the pair's largest unoccupied area of p-space.
A large literature describes the use of robots' physical bodies to support communication with people.Touch is a natural channel for physical interaction, yet it is not understood how principles of interpersonal touch might carry over to a robot.Exploring how interpersonal rules surrounding body accessibility and touch apply to a robot is critical toward understanding the extent to which people treat the act of touching body regions as a sign of closeness-even if the body belongs to a robotand is important to the field of humanoid social robotics.Thirty-one students participated in an interactive anatomy lesson with a small, humanoid robot.Participants either touched or pointed to an anatomical region of the robot in each of 26 trials while their skin conductance response was measured.Touching less accessible regions of a robot's body (e.g., its buttocks and genitals) was more physiologically arousing than touching more accessible regions (e.g., its hands and feet).No differences in physiological arousal were found when just pointing to those same anatomical regions.A social robot elicited tactile responses in human physiology, a result that signals people treat touching body parts as an act of closeness in itself that does not require a human recipient.The power of touching a humanoid body with identifiable body parts should caution mechanical and interaction designers about the positive and negative effects of human-robot interaction.
We are happy to present this Special Issue on Education in Human-Robot Interaction (HRI) to the community. As HRI has matured as a field, it is also becoming an increasingly popular educational topic and resource at all levels of instruction, from elementary through graduate programs. While several excellent review articles for the field exist, there is no textbook or recognized curriculum in HRI. The interdisciplinary nature of the field presents students and instructors with opportunities for building on diverse perspectives from design, engineering, computer science, and the social sciences and humanities, as well as challenges in presenting and working with material from such a broad array of disciplines. The authors in this special issue discuss their experiences with and strategies for designing HRI curricula and teaching HRI to students of diverse backgrounds and skill sets. We hope this special issue will inspire many more courses, summer schools, and educational outreach activities in HRI. We also hope that it sparks more discussions about diverse approaches to and necessary standards for HRI curricula.
Robotics and human-robot interaction (HRI) are growing fields that may benefit from an expanded perspective stimulated by more interdisciplinary contributions. One way to achieve this goal is to attract non-traditional students from the social sciences and humanities into these fields. This present paper describes two educational initiatives that focused on teaching non-engineering students about robotics and HRI. In one initiative, a group of younger students, including those with autism spectrum disorder (ASD), received hands-on experience with robotics in a context that was not overly technical, while in the other initiative, college students in the social sciences and humanities learned about basic HRI concepts and developed robotics applications. Themes common to both initiatives were to reach non-technical students who are not traditional targets for robotics education and to focus their learning on creating interactive sequences for robots based on key HRI design considerations rather than on the underlying mechanical and electrical details related to how those sequences are enacted inside the robot. Both initiatives were successful in terms of producing desired learning outcomes and fostering participant enjoyment.
We are happy to present this Special Issue on Education in Human-Robot Interaction (HRI) to the community. As HRI has matured as a field, it is also becoming an increasingly popular educational topic and resource at all levels of instruction, from elementary through graduate programs. While several excellent review articles for the field exist, there is no textbook or recognized curriculum in HRI. The interdisciplinary nature of the field presents students and instructors with opportunities for building on diverse perspectives from design, engineering, computer science, and the social sciences and humanities, as well as challenges in presenting and working with material from such a broad array of disciplines. The authors in this special issue discuss their experiences with and strategies for designing HRI curricula and teaching HRI to students of diverse backgrounds and skill sets. We hope this special issue will inspire many more courses, summer schools, and educational outreach activities in HRI. We also hope that it sparks more discussions about diverse approaches to and necessary standards for HRI curricula.
This article examines a cross-disciplinary approach to learning human-robot interaction (HRI) through real-world problem solving. The problem originated from the need of archaeologists at the University of California, Berkeley, and Ryerson University to safely explore archaeologically significant areas disturbed by heavy looting activities at the ancient site of el-Hibeh, Egypt. The learning objectives were developed through interdisciplinary collaboration of three departments at Ryerson University. The deliverable was an HRI final examination---known as the BUSA Dig---in which students teleoperated a robot of their own design and manufacture that explored and mapped a simulated archaeological site. The students participated in the examination through their membership in one of six mixed groups composed of undergraduate computer science and graduate digital media students. At the end of the exam, students were expected to understand and explain HRI principles, paradigms, and metrics, construct appropriate robots that could survive and function in a defined environment, and employ mobile and teleoperated robots that solved problems.
This article reviews the state of the art in social eye gaze for human-robot interaction (HRI). It establishes three categories of gaze research in HRI, defined by differences in goals and methods: a human-centered approach, which focuses on people's responses to gaze; a design-centered approach, which addresses the features of robot gaze behavior and appearance that improve interaction; and a technology-centered approach, which is concentrated on the computational tools for implementing social eye gaze in robots. This paper begins with background information about gaze research in HRI and ends with a set of open questions.
Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.
The present research examines how a robot's physical anthropomorphism interacts with perceived ability of robots to impact the level of realistic and identity threat that people perceive from robots and how it affects their support for robotics research. Experimental data revealed that participants perceived robots to be significantly more threatening to humans after watching a video of an android that could allegedly outperform humans on various physical and mental tasks relative to a humanoid robot that could do the same. However, when participants were not provided with information about a new generation of robots' ability relative to humans, then no significant differences were found in perceived threat following exposure to either the android or humanoid robots. Similarly, participants also expressed less support for robotics research after seeing an android relative to a humanoid robot outperform humans. However, when provided with no information about robots' ability relative to humans, then participants showed marginally decreased support for robotics research following exposure to the humanoid relative to the android robot. Taken together, these findings suggest that very humanlike robots can not only be perceived as a realistic threat to human jobs, safety, and resources, but can also be seen as a threat to human identity and uniqueness, especially if such robots also outperform humans. We also demonstrate the potential downside of such robots to the public's willingness to support and fund robotics research.
