Field Of Human-robot Interaction Research Articles

The Tactile Ethics of Soft Robotics: Designing Wisely for Human-Robot Interaction.

Soft robots promise an exciting design trajectory in the field of robotics and human-robot interaction (HRI), promising more adaptive, resilient movement within environments as well as a safer, more sensitive interface for the objects or agents the robot encounters. In particular, tactile HRI is a critical dimension for designers to consider, especially given the onrush of assistive and companion robots into our society. In this article, we propose to surface an important set of ethical challenges for the field of soft robotics to meet. Tactile HRI strongly suggests that soft-bodied robots balance tactile engagement against emotional manipulation, model intimacy on the bonding with a tool not with a person, and deflect users from personally and socially destructive behavior the soft bodies and surfaces could normally entice.

Simulation modeling of pedestrian behavior in the presence of unmanned mobile robots

Interactions between pedestrians and robots are becoming more commonplace. In public areas, for example, robots may be used for information dissemination, security, or patrol tasks. Based upon existing literature in the field of human-robot interaction, the ISAPT simulation system was revised to model individual pedestrian behavior in the presence of a mobile robot. Using an agent-based modeling approach, pedestrians are statistically assigned one of six reported behaviors when a robot is encountered: interact, watch, curious, ignore, cautious, and avoid. The modeling methods for incorporating these behaviors include modifying a pedestrian's existing agenda and/or their perception of the threat represented by the non-humanoid robot, while the pedestrian continues to make navigation decisions based on their overall utility function. This paper discusses the implementation of this capability and presents results on ISAPT's ability to reproduce the different behaviors reported in the literature. Data collected in a field study are used to further validate the system by comparing measures from observed behaviors to simulation output. Validation measures included lateral distance to robot and lateral path deviation. These results illustrate this approach is an effective means for adding this capability to microsimulation modeling systems.

Persistence of the uncanny valley: the influence of repeated interactions and a robot's attitude on its perception.

The uncanny valley theory proposed by Mori has been heavily investigated in the recent years by researchers from various fields. However, the videos and images used in these studies did not permit any human interaction with the uncanny objects. Therefore, in the field of human-robot interaction it is still unclear what, if any, impact an uncanny-looking robot will have in the context of an interaction. In this paper we describe an exploratory empirical study using a live interaction paradigm that involved repeated interactions with robots that differed in embodiment and their attitude toward a human. We found that both investigated components of the uncanniness (likeability and eeriness) can be affected by an interaction with a robot. Likeability of a robot was mainly affected by its attitude and this effect was especially prominent for a machine-like robot. On the other hand, merely repeating interactions was sufficient to reduce eeriness irrespective of a robot's embodiment. As a result we urge other researchers to investigate Mori's theory in studies that involve actual human-robot interaction in order to fully understand the changing nature of this phenomenon.

Walking in the uncanny valley: importance of the attractiveness on the acceptance of a robot as a working partner.

The Uncanny valley hypothesis, which tells us that almost-human characteristics in a robot or a device could cause uneasiness in human observers, is an important research theme in the Human Robot Interaction (HRI) field. Yet, that phenomenon is still not well-understood. Many have investigated the external design of humanoid robot faces and bodies but only a few studies have focused on the influence of robot movements on our perception and feelings of the Uncanny valley. Moreover, no research has investigated the possible relation between our uneasiness feeling and whether or not we would accept robots having a job in an office, a hospital or elsewhere. To better understand the Uncanny valley, we explore several factors which might have an influence on our perception of robots, be it related to the subjects, such as culture or attitude toward robots, or related to the robot such as emotions and emotional intensity displayed in its motion. We asked 69 subjects (N = 69) to rate the motions of a humanoid robot (Perceived Humanity, Eeriness, and Attractiveness) and state where they would rather see the robot performing a task. Our results suggest that, among the factors we chose to test, the attitude toward robots is the main influence on the perception of the robot related to the Uncanny valley. Robot occupation acceptability was affected only by Attractiveness, mitigating any Uncanny valley effect. We discuss the implications of these findings for the Uncanny valley and the acceptability of a robotic worker in our society.

Considering the effects of gender in child-robot interaction studies: comment on Srinivasan, et Al. (2013).

Using a pretest-posttest design, Srinivasan, et al. (2013 ) found that a period of interaction between children and an Isobot humanoid robot improved performance on standardized measures of imitation, planning, and execution of motor behaviors. The authors conducted their study with 15 typically developing children (9 boys, 6 girls) and 1 boy with autism. All participants were between the ages of 4 and 7 years. While considerations of gender expectations, norms, and appearance are now considered critical to social interactions between humans and robots by most researchers in the field of human-robot interactions, Srinivasan et al. did not consider these effects. This paper proposes that gender could have significant effects on the results of future work conducted in this area.

Developing a Dividual Model Using a Modular Neural Network for Human-Robot Interaction

Currently, in the field of human-robot interaction (HRI), robots have a problem that can only interact the same at all times with humans. In this paper, therefore, we introduce the concept called a dividual and build a model of the dividual to grow through interactions with others. In addition, using a modular neural network and reinforcement learning (actor-critic), we confirmed the process to choose an appropriate dividual out of plural dividuals.

Simultaneous people tracking and motion pattern learning

The field of Human Robot Interaction (HRI) encompasses many difficult challenges as robots need a better understanding of human actions. Human detection and tracking play a major role in such scenarios. One of the main challenges is to track them with long term occlusions due to agile nature of human navigation. However, in general humans do not make random movements. They tend to follow common motion patterns depending on their intentions and environmental/physical constraints. Therefore, knowledge of such common motion patterns could allow a robotic device to robustly track people even with long term occlusions. On the other hand, once a robust tracking is achieved, they can be used to enhance common motion pattern models allowing robots to adapt to new motion patterns that could appear in the environment. Therefore, this paper proposes to learn human motion patterns based on Sampled Hidden Markov Model (SHMM) and simultaneously track people using a particle filter tracker. The proposed simultaneous people tracking and human motion pattern learning has not only improved the tracking robustness compared to more conservative approaches, it has also proven robustness to prolonged occlusions and maintaining identity. Furthermore, the integration of people tracking and on-line SHMM learning have led to improved learning performance. These claims are supported by real world experiments carried out on a robot with suite of sensors including a laser range finder.

The role of the mass matrix in the analysis of mechanical systems

This paper proposes a simple, intuitive method of analyzing and understanding the mass matrix of a mechanical system. With very little calculation, it is possible to determine four important values that describe the inertia and inertial coupling of a mechanism: the locked effective inertia, the force coupling, the free effective inertia, and the acceleration coupling. These values can be determined for a system formulated in terms of joint coordinates, but when used with systems formulated in terms of workspace coordinates, this work provides a unified method of determining important, well-established concepts such as effective mass (particularly important in the field of human-robot interaction) and dynamic isotropy (an important consideration for robotic manipulators and haptic devices). Two examples are provided which highlight the use of this method to analyze robotic manipulators.

A Robot Centric Perspective on the HRI Paradigm

The industrial revolution undoubtedly defined the role of machines in our society, and it directly shaped the paradigm for human machine interaction - a paradigm which was inherited by the field of Human Robot Interaction (HRI) as the machines became robots. This paper argues that, for a foreseeable set of interactions, reshaping this paradigm would result in more effective and more often successful interactions. This paper presents our Robot Centric paradigm for HRI. Evidence in the form of summaries of relevant literature and our past efforts in developing social-robotics enabling technology is presented to support our paradigm. A definition and a set of recommendations for designing the key enabling component, sociocontextual cues, of our paradigm are presented. Finally, empirical evidence generated through a number of experiments and field studies (N = 456 and N = 320) demonstrates our paradigm is both feasibly incorporated into HRI and moreover, yields significant contributions to the successfulness of a set of HRIs.

Measuring Human-Robots Interactions

Social Robotics is an interdisciplinary playground where researchers from sociology, psychology, neuroscience, and robotics meet to design one kind of future robot: the social robot. This challenge is simple to describe, but complex to achieve. The social robot can be a classical robot or a machine with sufficient resources and capabilities to receive and exchange information with humans, with the ultimate result of helping people in daily-life activities. Exchanges should be intuitive and easy: these two key characteristics strongly define the sociability of artificial agents. The system formed by a human and a social robot is hybrid by nature. How should we consider its communication and interactions as compared with a human-human system? Humans use all available sensory and motoric modalities to communicate and establish social relations. Human-human interaction has a vast literature base that continues to be expanded by communication scientists, psychologists, and neuroscientists among others. In humanrobot systems, however, the inherent asymmetries prevent researchers from directly borrowing classical human-human approaches. However, one can be inspired by these efforts when developing tools and techniques that observe and evaluate human-robot interaction (HRI). The fundamental question is whether the same, or similar, mechanisms that drive human-human interaction also drive human-robot interactions. Although the controllable, measurable, and observable nature of robots provides researchers with a potentially infinite set of experimental conditions, the field of HRI is nevertheless constrained by a shortage of objective measurement

Speaker Localization Based on Phase Detection of Vowel Fundamental Frequencies

Research on human-robot interaction has recently been getting an increasing amount of attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we present experiment of speaker localization using a microphone array and an ITD (Interaural Time Difference) method which finds the sound source by phase shift of two signals. Band pass filters are designed to get vowel fundamental frequencies. Phase sensitive detectors are applied to measure the phase differences of voice signal of different microphones. All circuits are constructed by FPAA (field programmable analog array). The proposed system can output speaker location in real-time with low power.

Towards an Interdisciplinary Understanding of Perspective for Human-Robot Teamwork

We provide a context within the converging fields of team cognition and human-robot interaction (HRI) where the idea of perspective may be able to provide a useful framework for design. Thus, we explore perspective as it has been discussed across disciplines. Our goal is to begin an exploration of how perspective can be appropriately conceptualized and potentially instantiated within the context of social robots and human-robot team interaction, framing theory from the human sciences for design.

Human–Robot Interaction

The field of human-robot interaction (HRI) addresses the design, understanding, and evaluation of robotic systems, which involve humans and robots interacting through communication. As the field matures, education of students becomes increasingly important. Courses in HRI provide the canonical set of knowledge and core skills that represent the current state of the field and permit the evolution of knowledge and methods to be transferred from research to a broad set of students. In addition, coursework in HRI creates a workforce capable of transferring HRI theory to practice. However, as would be expected with an emerging field, HRI courses are largely ad hoc. This article summarizes the discussion and findings from the Teaching Humans About Human-Robot Interaction workshop on the development of an HRI course for computer scientists and engineers.

Human-Robot Collaboration: A Literature Review and Augmented Reality Approach in Design

NASA's vision for space exploration stresses the cultivation of human-robotic systems. Similar systems are also envisaged for a variety of hazardous earthbound applications such as urban search and rescue. Recent research has pointed out that to reduce human workload, costs, fatigue driven error and risk, intelligent robotic systems will need to be a significant part of mission design. However, little attention has been paid to joint human-robot teams. Making human-robot collaboration natural and efficient is crucial. In particular, grounding, situational awareness, a common frame of reference and spatial referencing are vital in effective communication and collaboration. Augmented Reality (AR), the overlaying of computer graphics onto the real worldview, can provide the necessary means for a human-robotic system to fulfill these requirements for effective collaboration. This article reviews the field of human-robot interaction and augmented reality, investigates the potential avenues for creating natural human-robot collaboration through spatial dialogue utilizing AR and proposes a holistic architectural design for human-robot collaboration.

Human-Robot Factors: Robots in the Workplace

As we celebrate the 50th anniversary of HFES, this panel discussion presents the emerging field of human-robot interaction as a critical research area in human factors for the next 50 years. Robots in the workplace are poised to change our lives over the next 50 years much as computers have the past 5 decades. This panel gathers four experts with diverse experience in studying technology's effects upon work to discuss the implications of robotic technology for work environments. Topics include the cognitive, social and affective human characteristics that impact human-robot interaction, the potential impact of robotic technology in the workplace, and factors influencing acceptance of robots at work. The implications for design of robotic products and systems are also discussed.

Behavioral overlays for non-verbal communication expression on a humanoid robot

This research details the application of non-verbal communication display behaviors to an autonomous humanoid robot, including the use of proxemics, which to date has been seldom explored in the field of human-robot interaction. In order to allow the robot to communicate information non-verbally while simultaneously fulfilling its existing instrumental behavior, a “behavioral overlay” model that encodes this data onto the robot's pre-existing motor expression is developed and presented. The state of the robot's system of internal emotions and motivational drives is used as the principal data source for non-verbal expression, but in order for the robot to display this information in a natural and nuanced fashion, an additional para-emotional framework has been developed to support the individuality of the robot's interpersonal relationships with humans and of the robot itself. An implementation on the Sony QRIO is described which overlays QRIO's existing EGO architecture and situated schema-based behaviors with a mechanism for communicating this framework through modalities that encompass posture, gesture and the management of interpersonal distance.

Final Report for the DARPA/NSF Interdisciplinary Study on Human–Robot Interaction

As part of a Defense Advanced Research Projects Agency/National Science Foundation study on human-robot interaction (HRI), over sixty representatives from academia, government, and industry participated in an interdisciplinary workshop, which allowed roboticists to interact with psychologists, sociologists, cognitive scientists, communication experts and human-computer interaction specialists to discuss common interests in the field of HRI, and to establish a dialogue across the disciplines for future collaborations. We include initial work that was done in preparation for the workshop, links to keynote and other presentations, and a summary of the findings, outcomes, and recommendations that were generated by the participants. Findings of the study include-the need for more extensive interdisciplinary interaction, identification of basic taxonomies and research issues, social informatics, establishment of a small number of common application domains, and field experience for members of the HRI community. An overall conclusion of the workshop was expressed as the following-HRI is a cross-disciplinary area, which poses barriers to meaningful research, synthesis, and technology transfer. The vocabularies, experiences, methodologies, and metrics of the communities are sufficiently different that cross-disciplinary research is unlikely to happen without sustained funding and an infrastructure to establish a new HRI community.

Social Interactions in HRI: The Robot View

This paper explores the topic of human-robot interaction (HRI) from the perspective of designing sociable autonomous robots-robots designed to interact with people in a human-like way. There are a growing number of applications for robots that people can engage as capable creatures or as partners rather than tools, yet little is understood about how to best design robots that interact with people in this way. The related field of human-computer interaction (HCI) offers important insights, however autonomous robots are a very different technology from desktop computers. In this paper, we look at the field of HRI from an HCI perspective, pointing out important similarities yet significant differences that may ultimately make HRI a distinct area of inquiry. One outcome of this discussion is that it is important to view the design and evaluation problem from the robot's perspective as well as that of the human. Taken as a whole, this paper provides a framework with which to design and evaluate sociable robots from a HRI perspective.