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Story-Based Context and Control for Robotic and Human Interactive Motion
Abstract
This extended abstract outlines the research plans and previous work of a first year PhD student applying to the Creativity and Cognition Graduate Student Symposium. The applicant's research interest is in designing and implementing motion-based interactions with robots, where the study participant is primed for the interactions through various narratives. Past work is described as well as an outline for future progress. The applicant is particularly interested in generating expressive motion for robots originating with human movers, captured by sensors and video.
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Robots in human facing environments will move alongside human beings. This movement has both functional and expressive meaning and plays a crucial role in human perception of robots. Secondarily, how the robot is controlled – through methods like movement or programming and drivers like oneself or an algorithm – factors into human perceptions. This paper outlines the use of an embodied movement installation, “The Loop”, to understand perceptions generated between humans and various technological agents, including a NAO robot and a virtual avatar. Participants were questioned about their perceptions of control in the various agents. Initial results with human subjects demonstrate an increased likelihood to rate a robot and a robotic shadow as algorithmically controlled, versus a human performer and a human-shaped VR avatar which were more likely rated as human actor controlled or split between algorithm/human actor. Participants also showed a tendency to rate their own performance in the exercise as needing improvement. Qualitative data, collected in the form of text and drawings, was open-ended and abstract. Drawings of humans and geometric shapes frequently appeared, as did the words “mirror”, “movement”, and variations on the word “awareness”.
This paper describes an innovative approach for studying interaction between humans and care robots. Using live theatrical performance, we developed a play that depicts a plausible, future care scenario between a human and a socially assistive robot. We used an expanded version of the Godspeed Questionnaire to measure the audiences’ reactions to the robot, the observed interactions between the human and the robot, and their overall reactions to the performance. We present our results and propose a methodology and guidelines for using applied theatre as a platform to study human robot interaction (HRI). Unlike other HRI studies, the subject of our research is not the user who interacts with the robot but rather the audiences observing the HRI. We consider the technical and artistic challenges of designing and staging a believable care scenario that could potentially influence the perception and acceptance of care robots. This study marks a first step towards designing a robust framework for combining applied theatre with HRI research.
This paper discusses a novel approach towards socializing non-anthropomorphic robots, which harnesses the expert knowledge of dancers to develop abstract robot morphologies and their capacity to move in affective and expressive ways. We argue that movement offers a key to socializing non-anthropomorphic robots. Our Performative Body Mapping (PBM) method investigates the possibility of teaching a non-humanlike robot to move and interact by human movement experts. The paper outlines the conceptual framework of PBM and discusses an ongoing pilot study that engages professional dancers to study the relationship between abstract, simple morphologies and their potential to move in expressive, socially encoded ways.
Nonverbal communication plays an important role in coordinating teammates' actions for collaborative activities. In this paper, we explore the impact of non-verbal social cues and behavior on task performance by a human-robot team. We report our results from an experiment where naive human subjects guide a robot to perform a physical task using speech and gesture. Both self-report via questionnaire and behavioral analysis of video offer evidence to support our hypothesis that implicit non-verbal communication positively impacts human-robot task performance with respect to understandability of the robot, efficiency of task performance, and robustness to errors that arise from miscommunication.
There is a saying that 95% of communication is body language, but few robot systems today make effective use of that ubiquitous channel. Motion is an essential area of social communication that will enable robots and people to collaborate naturally, develop rapport, and seamlessly share environments. The proposed work presents a principled set of motion features based on the Laban Effort system, a widespread and extensively tested acting ontology for the dynamics of 'how' we enact motion. The features allow us to analyze and, in future work, generate expressive motion using position (x, y) and orientation (theta). We formulate representative features for each Effort and parameterize them on expressive motion sample trajectories collected from experts in robotics and theater. We then produce classifiers for different 'manners' of moving and assess the quality of results by comparing them to the humans labeling the same set of paths on Amazon Mechanical Turk. Results indicate that the machine analysis (41.7% match between intended and classified manner) achieves similar accuracy overall compared to a human benchmark (41.2% match). We conclude that these motion features perform well for analyzing expression in low degree of freedom systems and could be used to help design more effectively expressive mobile robots.
Abstract— This paper gives an overview of ROS, an open- source robot operating,system. ROS is not an operating,system in the traditional sense of process management,and scheduling; rather, it provides a structured communications layer above the host operating,systems,of a heterogenous,compute,cluster. In this paper, we discuss how ROS relates to existing robot software frameworks, and briefly overview some of the available application software,which,uses ROS.
Argues that the narrative is fruitful metaphor for examining and interpreting human action. The body of the essay deals with the narrative as an organizing principle. The author illustrates the principle by referring to studies on causality that show how random nonhuman stimulus events are interpreted as human actors performing in familiar stories. That is to say, a narratory principle operates to provide meaning to the often nonsystematic encounters and interactions experienced in everyday life. To illustrate how the narrative root metaphor may be employed in understanding nontrivial psychological problems, the author discusses the phenomenon of self-deception. From the observation that humans are authors of self-narratives and actors in self-narratives, the author shows how self-deceivers make use of epistemic skills to maintain or enhance their narrative identities. The author interprets self-deception as a narrative reconstruction in which the person is the agent of reconstruction. The author suggests that the study of virtue would be more rewarding if scientists replaced the popular templatic conceptions with the more humanistic conceptions embraced by the narrative root metaphor. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Robot Theater is a fairly new arena for researching Human Robot Interaction, however, in surveying research already conducted, we have identified eight lessons from Robot Theater that inform the design of social robots today. As an interdisciplinary field, we include examples spanning robotics researchers, acting theorists, cognitive neuroscientists, behavioral psychologists and dramaturgy literature. Lessons learned include (1) the importance of intentionality in action; (2)(3)(4) the relationship between embodiment, gesture, and emotional expression; (5) the bipolar sociability categorization between machine and agent; (6) the power of interaction partners to shape robot attributions; (7) the role of audience acknowledgement and feedback; (8) the power of humor to enhance interaction. Robotics has had a long history with the field of entertainment; even the word ‘robot' comes from the 1921 Czech play ‘R.U.R.' - we look forward to rigorous and continued research and cross-pollination between these domains.
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