Elizabeth Cha

Nonverbal Signaling for Non-Humanoid Robots During Human-Robot Collaboration

Non-humanoid robots are becoming increasingly utilized for collaborative tasks across many domains, including industrial and service settings. Collaborative tasks between the human and robot rely on each collaborators ability to effectively convey their mental state while accurately estimating and interpreting their partners knowledge, intent, and actions. My research focuses on nonverbal communication signals that a non-humanoid robot can utilize during human-robot collaboration. We focus on motion, light and sound as they are commonly used communication channels across many domains and are available on most robot platforms. As a first step towards this goal, I present a completed study exploring how to use a simple multimodal light and sound signal to request help during a collaborative task. We then discuss future work to generate and utilize more complex signals to convey a variety of statuses to improve collaboration.

Using nonverbal signals to request help during human-robot collaboration

Non-humanoid robots are becoming increasingly utilized for collaborative tasks that rely on each collaborators ability to effectively convey their mental state while accurately estimating and interpreting their partners knowledge, intent, and actions. During these tasks, it may be beneficial or even necessary for the human collaborator to assist the robot. Consequently, we explore the use of nonverbal signals to request help during a collaborative task. We focus on light and sound as they are commonly used communication channels across many domains. This paper analyzes the effectiveness of three nonverbal help signals that vary in urgency. Our results show that these signals significantly influence the human collaborators and their perception of the collaboration.

A Survey of Nonverbal Signaling Methods for Non-Humanoid Robots

This monograph surveys and informs the design and usage of nonverbal signals for human-robot interaction. With robots increasingly being utilized for tasks that require them to not only operate in close proximity to humans but to interact with them as well, there has been great interest in the communication challenges associated with the varying degrees of interaction in these environments. The success of such interactions depends on robots’ ability to convey information about their knowledge, intent, and actions to co-located humans. The monograph presents a comprehensive review of literature related to the generation and usage of nonverbal signals that facilitate legibility of non-humanoid robot state and behavior. To motivate the need for these signaling behaviors, it surveys literature in human communication and psychology and outlines target use cases of non-humanoid robots. Specifically, the focus is on works that provide insight into the cognitive processes that enable humans to recognize, interpret, and exploit nonverbal signals. From these use cases, information is identified that is potentially important for non-humanoid robots to signal and organize it into three categories of robot state. The monograph then presents a review of signal design techniques to illustrate how signals conveying this information can be generated and utilized. It concludes by discussing issues that must be considered during nonverbal signaling and open research areas, with a focus on informing the design and usage of generalizable nonverbal signaling behaviors for task-oriented non-humanoid robots.

Designing telepresence robots for K-12 education

Telepresence robots have the potential to improve access to K-12 education for students who are unable to attend school for a variety of reasons. Since previous telepresence research has largely focused on the needs of adult users in workplace settings, it is unknown what challenges must be addressed for these robots to be effective tools in classrooms. In this paper, we seek to better understand how a telepresence robot should function in the classroom when operated by a remote student. Toward this goal, we conducted field sessions in which four designers operated a telepresence robot in a real K-12 classroom. Using the results, we identify key research challenges and present design insights meant to inform the HRI community in particular and robot designers in general.

Effects of Robot Sound on Auditory Localization in Human-Robot Collaboration

Auditory cues facilitate situational awareness by enabling humans to infer what is happening in the nearby environment. Unlike humans, many robots do not continuously produce perceivable state-expressive sounds. In this work, we propose the use of iconic auditory signals that mimic the sounds produced by a robot»s operations. In contrast to artificial sounds (e.g., beeps and whistles), these signals are primarily functional, providing information about the robot»s actions and state. We analyze the effects of two variations of robot sound, tonal and broadband, on auditory localization during a human-robot collaboration task. Results from 24 participants show that both signals significantly improve auditory localization, but the broadband variation is preferred by participants. We then present a computational formulation for auditory signaling and apply it to the problem of auditory localization using a human-subjects data collection with 18 participants to learn optimal signaling policies.

Evaluating the Effects of Personalized Appearance on Telepresence Robots for Education

Telepresence robots hold the potential to allow absent students to remain physically embodied and socially connected in the classroom. In this work, we investigate the effects of telepresence robot personalization on K-12 students» perceptions of the robot, perceptions of themselves, and feelings of self-presence. We conducted a between-subjects, 2-condition user study (N=24) on robot personalization. In this study, 9- to 13-year-old participants remotely completed an educational exercise using a telepresence robot. Lessons learned from this study will inform our continued work on using remote presence robots to preserve the educational and social experiences of students during extended absences from school.

My classroom robot: Exploring telepresence for K-12 education in a virtual environment

Telepresence robots have the potential to improve access to K-12 education. However, designing robots for classroom use presents unique challenges from both logistical and technological perspectives. To address these challenges, we created My Classroom Robot, an interactive game in which players can operate a virtual telepresence robot in a classroom environment. The virtual classroom environment allows us to collect data and prototype different designs prior to involving the high overhead required in going into the real classroom. In this work, we present the design of My Classroom Robot, an initial evaluation, and the lessons learned from its development.

ModLight: Designing a modular light signaling tool for human-robot interaction

Recent work has shown the potential for lights to act as simple, yet expressive signaling mechanisms for use in a variety of human-robot applications. However, the wide range of robot shapes and sizes makes it difficult for researchers to quickly prototype and evaluate different light configurations and signal designs. In this work, we present the design of ModLight, a modular research tool consisting of a set of low cost light blocks that can be easily reconfigured to fit a myriad of robots and applications. ModLight also provides researchers, designers, and students with open-source software tools that enable them to visually design new signals and easily integrate them into existing systems. This work also serves to motivate the need for further research in developing light behaviors for use in human-robot interaction. Towards this goal, we present our design rationale including a brief analysis of the signaling needs of several robots and applications.