scholarly journals A dataset of human and robot approach behaviors into small free-standing conversational groups

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247364
Author(s):  
Fangkai Yang ◽  
Yuan Gao ◽  
Ruiyang Ma ◽  
Sahba Zojaji ◽  
Ginevra Castellano ◽  
...  
Keyword(s):  
Virtual Environments ◽  
Human Robot Interaction ◽  
Limiting Factor ◽  
Free Standing ◽  
Robot Interaction ◽  
Natural Interfaces ◽  
Human Capabilities ◽  
Approach Behaviors ◽  
Perception Of Robots ◽  
Full Body

The analysis and simulation of the interactions that occur in group situations is important when humans and artificial agents, physical or virtual, must coordinate when inhabiting similar spaces or even collaborate, as in the case of human-robot teams. Artificial systems should adapt to the natural interfaces of humans rather than the other way around. Such systems should be sensitive to human behaviors, which are often social in nature, and account for human capabilities when planning their own behaviors. A limiting factor relates to our understanding of how humans behave with respect to each other and with artificial embodiments, such as robots. To this end, we present CongreG8 (pronounced ‘con-gre-gate’), a novel dataset containing the full-body motions of free-standing conversational groups of three humans and a newcomer that approaches the groups with the intent of joining them. The aim has been to collect an accurate and detailed set of positioning, orienting and full-body behaviors when a newcomer approaches and joins a small group. The dataset contains trials from human and robot newcomers. Additionally, it includes questionnaires about the personality of participants (BFI-10), their perception of robots (Godspeed), and custom human/robot interaction questions. An overview and analysis of the dataset is also provided, which suggests that human groups are more likely to alter their configuration to accommodate a human newcomer than a robot newcomer. We conclude by providing three use cases that the dataset has already been applied to in the domains of behavior detection and generation in real and virtual environments. A sample of the CongreG8 dataset is available at https://zenodo.org/record/4537811.

Similarity, Complementarity, and Agency in HRI

2016 ◽  
Vol 60 (1) ◽  
pp. 1230-1234 ◽  
Author(s):  
Samantha F. Warta ◽  
Katelynn A. Kapalo ◽  
Andrew Best ◽  
Stephen M. Fiore
Keyword(s):  
Cognitive Processes ◽  
Social Cognitive ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Human Capabilities ◽  
Design Elements ◽  
Social Settings ◽  
Perception Of Robots ◽  
Research Questions ◽  
Human Robot Collaboration

Robotic teammates are becoming prevalent in increasingly complex and dynamic operational and social settings. For this reason, the perception of robots operating in such environments has transitioned from the perception of robots as tools, extending human capabilities, to the perception of robots as teammates, collaborating with humans and displaying complex social cognitive processes. The goal of this paper is to introduce a discussion on an integrated set of robotic design elements, as well as provide support for the idea that human-robot interaction requires a clearer understanding of social cognitive constructs to optimize human-robot collaboration. We develop a set of research questions addressing these constructs with the goal of improving the engineering of artificial cognitive systems reliant on natural human-robot interaction.

Impacts of Multimodal Feedback on Efficiency of Proactive Information Retrieval from Task-Related HRI

2012 ◽  
Vol 16 (2) ◽  
pp. 313-326 ◽  
Author(s):  
Barbara Gonsior ◽  
◽  
Christian Landsiedel ◽  
Nicole Mirnig ◽  
Stefan Sosnowski ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Visual Space ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Multimodal Feedback ◽  
Goal Location ◽  
Approach Behaviors ◽  
First Results ◽  
Robot Head ◽  
Feedback Modalities

This work is a first step towards an integration ofmultimodality with the aim to make efficient use of both human-like, and non-human-like feedback modalities in order to optimize proactive information retrieval from task-related Human-Robot Interaction (HRI) in human environments. The presented approach combines the human-like modalities speech and emotional facial mimicry with non-human-like modalities. The proposed non-human-like modalities are a screen displaying retrieved knowledge of the robot to the human and a pointer mounted above the robot head for pointing directions and referring to objects in shared visual space as an equivalent for arm and hand gestures. Initially, pre-interaction feedback is explored in an experiment investigating different approach behaviors in order to find socially acceptable trajectories to increase the success of interactions and thus efficiency of information retrieval. Secondly, pre-evaluated humanlike modalities are introduced. First results of a multimodal feedback study are presented in the context of the IURO project,1where a robot asks for its way to a predefined goal location.1. Interactive Urban Robot, http://www.iuro-project.eu

Human-Robot Interaction Design: Understanding User Needs and Requirements

2005 ◽  
Vol 49 (3) ◽  
pp. 447-451 ◽  
Author(s):  
Julie A. Adams
Keyword(s):  
Interaction Design ◽  
Task Analysis ◽  
Qualitative Evaluation ◽  
Human Robot Interaction ◽  
User Needs ◽  
User Centered Design ◽  
Robot Interaction ◽  
Human Capabilities ◽  
Goal Hierarchy ◽  
Preliminary Communication

Goal-Directed Task Analysis is being applied to assessing the needs and requirements for developing novel techniques and tools to permit a small number of humans to supervise large robotic teams. The paper presents a preliminary overall goal hierarchy as well as a preliminary communication goal hierarchy based upon the initial analysis. This research involves working directly with the Nashville Metro Police department's Bomb Squad and the Nashville Metro Fire Department's HAZMAT team. The focus is the assessment of actual user needs and requirements employing well-defined user centered design practices in combination with Goal-Directed Task Analysis. The resulting Goal- Decision-SA structure will be employed to develop potential human-robot interaction designs for further qualitative and qualitative evaluation. The objective is to successfully integrate robots into the Chemical, Biological, Radiological, Nuclear and Explosive device search and rescue tasks such that the robots complement and augment the current human capabilities.

scholarly journals How Ethical Issues Raised by Human–Robot Interaction can Impact the Intention to use the Robot?

2022 ◽  
Author(s):  
Reza Etemad-Sajadi ◽  
Antonin Soussan ◽  
Théo Schöpfer
Keyword(s):  
Structural Equation ◽  
User Study ◽  
Ethical Issues ◽  
Human Robot Interaction ◽  
Equation Modeling ◽  
Intention To Use ◽  
Robot Interaction ◽  
Final Sample ◽  
Perception Of Robots ◽  
The Impact

AbstractThe goal of this research is to focus on the ethical issues linked to the interaction between humans and robots in a service delivery context. Through this user study, we want to see how ethics influence user’s intention to use a robot in a frontline service context. We want to observe the importance of each ethical attribute on user’s intention to use the robot in the future. To achieve this goal, we incorporated a video that showed Pepper, the robot, in action. Then respondents had to answer questions about their perception of robots based on the video. Based on a final sample of 341 respondents, we used structural equation modeling (SEM) to test our hypotheses. The results show that the most important ethical issue is the Replacement and its implications for labor. When we look at the impact of the ethical issues on the intention to use, we discovered that the variables impacting the most are Social cues, Trust and Safety.

scholarly journals Evaluating public opinion towards robots: a mixed-method approach

2019 ◽  
Vol 10 (1) ◽  
pp. 286-297
Author(s):  
Stefania Operto
Keyword(s):  
Significant Degree ◽  
Human Robot Interaction ◽  
Confirmatory Bias ◽  
Robot Interaction ◽  
Perception Of Robots ◽  
The One ◽  
Impact Of Technology ◽  
Degree Of Differentiation ◽  
The Impact ◽  
Research Show

AbstractThe article presents the results of some research conducted in Italy on the perception of robots. The study was carried out as part of a project arranged by the School of Robotics (Scuola di Robotica) in 2017/2018 and involved around 700 Italian citizens belonging to different social groups. Data collection used mixed methods: surveys, focus groups, interviews, and participatory workshops. The results were compared with surveys conducted in Europe by the Eurobarometer.Italy is an interesting context for this type of study for the density of robots, for the growth trends of robotics compared to other countries and for the relationships between industry and the labor market. The results of the research show that the attitudes and expectations of Italians towards robots are complex, multidimensional and contradictory: on the one hand, the interviewees positively value the growing presence of robots, on the other, they show fears about the spread of robotics in society. Robots, especially those designed to interact with humans, are part of a large system influenced by social, cultural and environmental factors in which actors move with different expectations and needs. The presence of a significant degree of differentiation between the responses of the different socio-demographic categories confirms the importance of investigating these issues, in order to reduce the distance that persists between researchers and scientists and the impact of technology on society. Furthermore, robotics is often narrated with myths and legends that have no correspondence in reality; since robots will interact more fully with humans, the human-robot interaction process and the bias integrated into the technology must be carefully studied to avoid the risks of confirmatory bias.

A Novel Cognitive Approach for Measuring the Trust in Robots

2019 ◽  
Vol 12 (3) ◽  
pp. 60-73
Author(s):  
Akash Dutt Dubey ◽  
Bimal Aklesh Kumar
Keyword(s):  
Path Planning ◽  
Empirical Evaluation ◽  
Trust Model ◽  
Human Robot Interaction ◽  
Learning Cycle ◽  
Cognitive Approach ◽  
Robot Interaction ◽  
Human Capabilities ◽  
Trust Relationship

One of the major challenges in human-robot interaction is to determine the trustworthiness of the robot. In order to enhance and augment the human capabilities by establishing a human robot partnership, it is important to evaluate the reliability and dependability of the robots for the specific tasks. The trust relationship between the human and robot becomes critical especially in the cases where there is strong cohesion between humans and robots. In this article, a cognition based-trust model has been developed which measures the trust and other related cognitive parameters of the robot. This trust model has been applied on a customized robot which performs path planning tasks using three different algorithms. The simulation of the model has been done to evaluate the trust of the robot for the three algorithms. The results show that with each learning cycle of each method, the trust of the robot increases. An empirical evaluation has also been done to validate the model.

Safety Perception and Behaviors during Human-Robot Interaction in Virtual Environments

2020 ◽  
Vol 64 (1) ◽  
pp. 2087-2091
Author(s):  
Daxton Mitchell ◽  
HeeSun Choi ◽  
Justin M. Haney
Keyword(s):  
Virtual Environments ◽  
Low Cost ◽  
Human Robot Interaction ◽  
Physical Interaction ◽  
Minimal Risk ◽  
Robot Interaction ◽  
Perceived Safety ◽  
Head Mounted Display ◽  
Safety Perception ◽  
And Behaviors

Virtual Reality (VR) technology is increasingly used to simulate and study human-robot interaction (HRI) because of its low cost and minimal risk to participants. The current study investigated whether perceived safety and safety-related behaviors during human-robot interaction can be adequately examined in virtual environments. Two prior studies that examined perceived safety and proxemics behavior during human-robot interaction in real environments were replicated in virtual environments using Head-Mounted Display (HMD) VR. Our results indicated that although perceived safety during virtual human-robot interaction is higher than during physical interaction in some situations, the virtual simulation of robots induced safety perception and behaviors comparable to those found in real environments and some of the findings of the previous human-robot interaction studies were replicable in a virtual environment. These findings suggest that VR simulation is a valid and useful method for research and worker training; however, it may be less sensitive than real environments.

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