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Social Robotics and Human-Robot Interaction (HRI)

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (10 November 2021) | Viewed by 30072

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Special Issue Editors

Prof. Dr. Koen Hindriks

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Guest Editor

Department of Computer Science, Vrije Universiteit (VU) Amsterdam, Amsterdam, Netherlands
Interests: socially-intelligent systems; cognitive agents; agent programming languages; human-robot interaction; multi-agent systems

Prof. Dr. An Jacobs

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Guest Editor

IMEC, Vrije Universiteit Brussel, Brussel, Belgium
Interests: sociology; digital technology; human robot interaction; human centred design; health care

Dr. Hoang-Long Cao

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Guest Editor

Department of Mechanical Engineering (MECH), Vrije Universiteit Brussel, Brussel, Belgium
Interests: mechatronics; robotics; human-robot interaction; cognitive robotics; automation & robotics; autonomous robot; humanoid robots; social robotics

Special Issue Information

Dear Colleagues,

Social robots are robots that offer support in a socially interactive way. Social robot applications are quickly maturing. Many off-the-shelf solutions have appeared, and some have disappeared over the last few years. They are studied from different disciplinary backgrounds (psychology, engineering, industry) and put into action in different domains (e.g., health, children, manufacturing) to research their applicability in real live social interactions.

Off-the-shelf prototypes of social robots are used in interaction outside the lab, being tested in the wild or in near “real life” environments to increase our understanding of the limitations and opportunities for social interaction these solutions can bring in the practices of a real life application. With this Special Issue, we are not only looking for success stories, but we are also particularly interested in the lessons learned from these first experiences in the wild. What hands-on advice can we collect by deploying and researching the application of social robots into a (semi-)real life environment? We are interested in receiving submissions on the following topics, but we do not limit you to them:

Case studies where things did not go as planned;
Challenges with reproducing human–human interaction findings in human–robot settings;
Lessons learnt for improving robot interaction design;
Comparative case studies of social robot use;
End user programming of social robots;
Long term use of social robots;
Typologies of social robots users;
Social robots with specific target groups;
Next steps in social robotics research.

Prof. Dr. Koen Hindriks
Prof. Dr. An Jacobs
Dr. Hoang-Long Cao
Guest Editors

Manuscript Submission Information

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Keywords

Social robots
Human-Robot Interaction
artificial intelligence
natural language understanding
robotics

Published Papers (7 papers)

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Research

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14 pages, 3116 KiB

Open AccessArticle

From When to When: Evaluating Naturalness of Reaction Time via Viewing Turn around Behaviors

by Atsumu Kubota, Mitsuhiko Kimoto, Takamasa Iio, Katsunori Shimohara and Masahiro Shiomi

Appl. Sci. 2021, 11(23), 11424; https://0-doi-org.brum.beds.ac.uk/10.3390/app112311424 - 02 Dec 2021

Viewed by 1827

Abstract

This paper addresses the effects of visual reaction times of a turn around behavior toward touch stimulus in the context of perceived naturalness. People essentially prefer a quick and natural reaction time to interaction partners, but appropriate reaction times will change due to the kinds of partners, e.g., humans, computers, and robots. In this study, we investigate two visual reaction times in touch interaction: the time length from the touched timing to the start of a reaction behavior, and the time length of the reaction behavior. We also investigated appropriate reaction times for different beings: three robots (Sota, Nao and Pepper) and humans (male and female). We conducted a web-survey based experiment to investigate natural reaction times for robots and humans, and the results concluded that the best combinations of both reaction times are different between each robot (i.e., among Sota, Nao and Pepper) and the humans (i.e., between male and female). We also compared the effect of using the best combinations for each robot and human to prove the importance of using each appropriate reaction timing for each being. The results suggest that an appropriate reaction time combination investigated from the male model is not ideal for robots, and the combination investigated from the female model is a better choice for robots. Our study also suggests that calibrating parameters for individual robots’ behavior design would enable better performances than using parameters of robot behaviors based on observing human-human interaction, although such an approach is a typical method of robot behavior design. Full article

(This article belongs to the Special Issue Social Robotics and Human-Robot Interaction (HRI))

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14 pages, 464 KiB

Open AccessArticle

A New Perspective on Robot Ethics through Investigating Human–Robot Interactions with Older Adults

by Anouk van Maris, Nancy Zook, Sanja Dogramadzi, Matthew Studley, Alan Winfield and Praminda Caleb-Solly

Appl. Sci. 2021, 11(21), 10136; https://0-doi-org.brum.beds.ac.uk/10.3390/app112110136 - 29 Oct 2021

Cited by 3 | Viewed by 3132

Abstract

This work explored the use of human–robot interaction research to investigate robot ethics. A longitudinal human–robot interaction study was conducted with self-reported healthy older adults to determine whether expression of artificial emotions by a social robot could result in emotional deception and emotional attachment. The findings from this study have highlighted that currently there appears to be no adequate tools, or the means, to determine the ethical impact and concerns ensuing from long-term interactions between social robots and older adults. This raises the question whether we should continue the fundamental development of social robots if we cannot determine their potential negative impact and whether we should shift our focus to the development of human–robot interaction assessment tools that provide more objective measures of ethical impact. Full article

(This article belongs to the Special Issue Social Robotics and Human-Robot Interaction (HRI))

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13 pages, 2133 KiB

Open AccessArticle

Modeling a Pre-Touch Reaction Distance around Socially Touchable Upper Body Parts of a Robot

by Dario Alfonso Cuello Mejía, Hidenobu Sumioka, Hiroshi Ishiguro and Masahiro Shiomi

Appl. Sci. 2021, 11(16), 7307; https://0-doi-org.brum.beds.ac.uk/10.3390/app11167307 - 09 Aug 2021

Cited by 3 | Viewed by 2482

Abstract

Although before-touch situations are essential to achieve natural touch interactions between people and robots, they receive less attention than after-touch situations. This study reports pre-touch reaction distance analysis results around touchable upper body parts, i.e., shoulders, elbows, and hands, based on human–human pre-touch interaction. We also analyzed the effects of gender, approach side, speed, and acclimation in modeling the pre-touch reaction distance, and found that the distance around the hands is smaller than the distance around the shoulders and elbows, and speed and acclimation affect the distance. On the other hand, gender and approach side do not significantly affect the pre-touch reaction distance. Finally, we implemented the results in a male-looking android and confirmed that it reacted toward pre-touch based on the obtained model. Full article

(This article belongs to the Special Issue Social Robotics and Human-Robot Interaction (HRI))

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21 pages, 19532 KiB

Open AccessArticle

Skeleton Tracking Accuracy and Precision Evaluation of Kinect V1, Kinect V2, and the Azure Kinect

by Michal Tölgyessy, Martin Dekan and Ľuboš Chovanec

Appl. Sci. 2021, 11(12), 5756; https://0-doi-org.brum.beds.ac.uk/10.3390/app11125756 - 21 Jun 2021

Cited by 49 | Viewed by 8089

Abstract

The Azure Kinect, the successor of Kinect v1 and Kinect v2, is a depth sensor. In this paper we evaluate the skeleton tracking abilities of the new sensor, namely accuracy and precision (repeatability). Firstly, we state the technical features of all three sensors, since we want to put the new Azure Kinect in the context of its previous versions. Then, we present the experimental results of general accuracy and precision obtained by measuring a plate mounted to a robotic manipulator end effector which was moved along the depth axis of each sensor and compare them. In the second experiment, we mounted a human-sized figurine to the end effector and placed it in the same positions as the test plate. Positions were located 400 mm from each other. In each position, we measured relative accuracy and precision (repeatability) of the detected figurine body joints. We compared the results and concluded that the Azure Kinect surpasses its discontinued predecessors, both in accuracy and precision. It is a suitable sensor for human–robot interaction, body-motion analysis, and other gesture-based applications. Our analysis serves as a pilot study for future HMI (human–machine interaction) designs and applications using the new Kinect Azure and puts it in the context of its successful predecessors. Full article

(This article belongs to the Special Issue Social Robotics and Human-Robot Interaction (HRI))

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19 pages, 3993 KiB

Open AccessArticle

A Human-Inspired Control Strategy for Improving Seamless Robot-To-Human Handovers

by Paramin Neranon and Tanapong Sutiphotinun

Appl. Sci. 2021, 11(10), 4437; https://0-doi-org.brum.beds.ac.uk/10.3390/app11104437 - 13 May 2021

Cited by 4 | Viewed by 2484

Abstract

One of the challenging aspects of robotics research is to successfully establish a human-like behavioural control strategy for human–robot handover, since a robotic controller is further complicated by the dynamic nature of the human response. This paper consequently highlights the development of an appropriate set of behaviour-based control for robot-to-human object handover by first understanding an equivalent human–human handover. The optimized hybrid position and impedance control was implemented to ensure good stability, adaptability and comfort of the robot in the object handover tasks. Moreover, a questionnaire technique was employed to gather information from the participants concerning their evaluations of the developed control system. The results demonstrate that the quantitative measurement of performance of the human-inspired control strategy can be considered acceptable for seamless human–robot handovers. This also provided significant satisfaction with the overall control performance in the robotic control system, in which the robot can dexterously pass the object to the receiver in a timely and natural manner without the risk of harm or injury by the robot. Furthermore, the survey responses were in agreement with the parallel test outcomes, demonstrating significant satisfaction with the overall performance of the robot–human interaction, as measured by an average rating of 4.20 on a five-point scale. Full article

(This article belongs to the Special Issue Social Robotics and Human-Robot Interaction (HRI))

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27 pages, 4279 KiB

Open AccessArticle

Coordinating Entrainment Phenomena: Robot Conversation Strategy for Object Recognition

by Mitsuhiko Kimoto, Takamasa Iio, Masahiro Shiomi and Katsunori Shimohara

Appl. Sci. 2021, 11(5), 2358; https://0-doi-org.brum.beds.ac.uk/10.3390/app11052358 - 07 Mar 2021

Cited by 2 | Viewed by 1991

Abstract

This study proposes a robot conversation strategy involving speech and gestures to improve a robot’s indicated object recognition, i.e., the recognition of an object indicated by a human. Research conducted to improve the performance of indicated object recognition is divided into two main approaches: development and interactive. The development approach addresses the development of new devices or algorithms. Through human–robot interaction, the interactive approach improves the performance by decreasing the variability and the ambiguity of the references. Inspired by the findings of entrainment and entrainment inhibition, this study proposes a robot conversation strategy that utilizes the interactive approach. While entrainment is a phenomenon in which people unconsciously tend to mimic words and/or gestures of their interlocutor, entrainment inhibition is the opposite phenomenon in which people decrease the amount of information contained in their words and gestures when their interlocutor provides excess information. Based on these phenomena, we designed a robot conversation strategy that elicits clear references. We experimentally compared this strategy with the other interactive strategy in which a robot explicitly requests clarifications when a human refers to an object. We obtained the following findings: (1) The proposed strategy clarifies human references and improves indicated object recognition performance, and (2) the proposed strategy forms better impressions than the other interactive strategy that explicitly requests clarifications when people refer to objects. Full article

(This article belongs to the Special Issue Social Robotics and Human-Robot Interaction (HRI))

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Review

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23 pages, 4016 KiB

Open AccessFeature PaperReview

Social Robots in Hospitals: A Systematic Review

by Carina Soledad González-González, Verónica Violant-Holz and Rosa Maria Gil-Iranzo

Appl. Sci. 2021, 11(13), 5976; https://0-doi-org.brum.beds.ac.uk/10.3390/app11135976 - 27 Jun 2021

Cited by 28 | Viewed by 7374

Abstract

Hospital environments are facing new challenges this century. One of the most important is the quality of services to patients. Social robots are gaining prominence due to the advantages they offer; in particular, several of their main uses have proven beneficial during the pandemic. This study aims to shed light on the current status of the design of social robots and their interaction with patients. To this end, a systematic review was conducted using WoS and MEDLINE, and the results were exhaustive analyzed. The authors found that most of the initiatives and projects serve the elderly and children, and specifically, that they helped these groups fight diseases such as dementia, autism spectrum disorder (ASD), cancer, and diabetes. Full article

(This article belongs to the Special Issue Social Robotics and Human-Robot Interaction (HRI))

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