scholarly journals Human-Robot Interaction for Semi-Autonomous Assistive Robots : Empirical Studies and an Interaction Concept for Supporting Elderly People at Home

2014 ◽  
Author(s):  
Marcus Mast ◽  
Keyword(s):  
Elderly People ◽  
Empirical Studies ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Assistive Robots ◽  
At Home

scholarly journals Towards a communication model for a sociable companion robot

2021 ◽  
Author(s):  
Lauren Dwyer
Keyword(s):  
Human Robot Interaction ◽  
Communication Model ◽  
Robot Interaction ◽  
The Public ◽  
Assistive Robots ◽  
Technical Requirements ◽  
Long Term Study ◽  
Robot Evaluation ◽  
Socially Assistive Robot

Anxiety has a lifetime prevalence of 31% of Canadians (Katzman et al. 2014). In Canada, psychological services are only covered by provincial health insurance if the psychologist is employed in the public sector; this means long wait times in the public system or expensive private coverage (Canadian Psychological Association). Currently, social robots and Socially Assistive Robots (SAR) are used in the treatment of elderly individuals in nursing homes, as well as children with autism (Feil-Seifer & Matarić, 2011; Tapus et al., 2012). The following MRP is the first step in a long-term project that will contend with the issues faced by individuals with anxiety using a combined communications, social robotics, and mental health approach to develop an anxiety specific socially assistive robot companion. The focus of this MRP is the development of a communication model that includes three core aspects of a social robot companion: Human-Robot Interaction (HRI), anxiety disorders, and technical design. The model I am developing will consist of a series of suggestions for the robot that could be implemented in a long-term study. The model will include suggestions towards the design, communication means, and technical requirements, as well as a model for evaluating the robot from a Human-Robot- Interaction perspective. This will be done through an evaluation of three robots, Sphero’s BB-8 App Enabled Droid, Aldebaran’s Nao, and the Spin Master Zoomer robot. Evaluation measures include modified versions of Shneiderman’s (1992) evaluation of human-factors goals, Feil-Seifer et al.’s (2007) SAR evaluative questions, prompts for the description of both the communication methods and the physical characteristics, and a record of the emotional response of the user when interacting with the robot.

scholarly journals Towards a communication model for a sociable companion robot

2021 ◽  
Author(s):  
Lauren Dwyer
Keyword(s):  
Human Robot Interaction ◽  
Communication Model ◽  
Robot Interaction ◽  
The Public ◽  
Assistive Robots ◽  
Technical Requirements ◽  
Long Term Study ◽  
Robot Evaluation ◽  
Socially Assistive Robot

Anxiety has a lifetime prevalence of 31% of Canadians (Katzman et al. 2014). In Canada, psychological services are only covered by provincial health insurance if the psychologist is employed in the public sector; this means long wait times in the public system or expensive private coverage (Canadian Psychological Association). Currently, social robots and Socially Assistive Robots (SAR) are used in the treatment of elderly individuals in nursing homes, as well as children with autism (Feil-Seifer & Matarić, 2011; Tapus et al., 2012). The following MRP is the first step in a long-term project that will contend with the issues faced by individuals with anxiety using a combined communications, social robotics, and mental health approach to develop an anxiety specific socially assistive robot companion. The focus of this MRP is the development of a communication model that includes three core aspects of a social robot companion: Human-Robot Interaction (HRI), anxiety disorders, and technical design. The model I am developing will consist of a series of suggestions for the robot that could be implemented in a long-term study. The model will include suggestions towards the design, communication means, and technical requirements, as well as a model for evaluating the robot from a Human-Robot- Interaction perspective. This will be done through an evaluation of three robots, Sphero’s BB-8 App Enabled Droid, Aldebaran’s Nao, and the Spin Master Zoomer robot. Evaluation measures include modified versions of Shneiderman’s (1992) evaluation of human-factors goals, Feil-Seifer et al.’s (2007) SAR evaluative questions, prompts for the description of both the communication methods and the physical characteristics, and a record of the emotional response of the user when interacting with the robot.

Managing workload in human–robot interaction: A review of empirical studies

2010 ◽  
Vol 26 (5) ◽  
pp. 840-856 ◽  
Author(s):  
Matthew S. Prewett ◽  
Ryan C. Johnson ◽  
Kristin N. Saboe ◽  
Linda R. Elliott ◽  
Michael D. Coovert
Keyword(s):  
Empirical Studies ◽  
Human Robot Interaction ◽  
Robot Interaction

scholarly journals Comply with Me: Using Design Manipulations to Affect Human–Robot Interaction in a COVID-19 Officer Robot Use Case

2021 ◽  
Vol 5 (11) ◽  
pp. 71
Author(s):  
Ela Liberman-Pincu ◽  
Amit David ◽  
Vardit Sarne-Fleischmann ◽  
Yael Edan ◽  
Tal Oron-Gilad
Keyword(s):  
Thematic Analysis ◽  
Face Mask ◽  
Human Robot Interaction ◽  
Use Case ◽  
Robot Interaction ◽  
Public Building ◽  
Assistive Robots ◽  
Socially Assistive Robots ◽  
Robotic Application

This study examines the effect of a COVID-19 Officer Robot (COR) on passersby compliance and the effects of its minor design manipulations on human–robot interaction. A robotic application was developed to ensure participants entering a public building comply with COVID restrictions of a green pass and wearing a face mask. The participants’ attitudes toward the robot and their perception of its authoritativeness were explored with video and questionnaires data. Thematic analysis was used to define unique behaviors related to human–COR interaction. Direct and extended interactions with minor design manipulation of the COR were evaluated in a public scenario setting. The results demonstrate that even minor design manipulations may influence users’ attitudes toward officer robots. The outcomes of this research can support manufacturers in rapidly adjusting their robots to new domains and tasks and guide future designs of authoritative socially assistive robots (SARs).

scholarly journals Use and usability of software verification methods to detect behaviour interference when teaching an assistive home companion robot: A proof-of-concept study

2021 ◽  
Vol 12 (1) ◽  
pp. 402-422
Author(s):  
Kheng Lee Koay ◽  
Matt Webster ◽  
Clare Dixon ◽  
Paul Gainer ◽  
Dag Syrdal ◽  
...  
Keyword(s):  
Software Verification ◽  
User Study ◽  
Human Robot Interaction ◽  
Proof Of Concept ◽  
Robot Interaction ◽  
Teaching System ◽  
Assistive Robots ◽  
Verification Methods ◽  
Smart Home Environment ◽  
Formal Behaviour

Abstract When studying the use of assistive robots in home environments, and especially how such robots can be personalised to meet the needs of the resident, key concerns are issues related to behaviour verification, behaviour interference and safety. Here, personalisation refers to the teaching of new robot behaviours by both technical and non-technical end users. In this article, we consider the issue of behaviour interference caused by situations where newly taught robot behaviours may affect or be affected by existing behaviours and thus, those behaviours will not or might not ever be executed. We focus in particular on how such situations can be detected and presented to the user. We describe the human–robot behaviour teaching system that we developed as well as the formal behaviour checking methods used. The online use of behaviour checking is demonstrated, based on static analysis of behaviours during the operation of the robot, and evaluated in a user study. We conducted a proof-of-concept human–robot interaction study with an autonomous, multi-purpose robot operating within a smart home environment. Twenty participants individually taught the robot behaviours according to instructions they were given, some of which caused interference with other behaviours. A mechanism for detecting behaviour interference provided feedback to participants and suggestions on how to resolve those conflicts. We assessed the participants’ views on detected interference as reported by the behaviour teaching system. Results indicate that interference warnings given to participants during teaching provoked an understanding of the issue. We did not find a significant influence of participants’ technical background. These results highlight a promising path towards verification and validation of assistive home companion robots that allow end-user personalisation.

Maximizing the Benefits of Participatory Design for Human–Robot Interaction Research With Older Adults

2021 ◽  
pp. 001872082110374
Author(s):  
Wendy A. Rogers ◽  
Travis Kadylak ◽  
Megan A. Bayles
Keyword(s):  
Older Adults ◽  
Participatory Design ◽  
Aging In Place ◽  
Human Robot Interaction ◽  
Multiple Stakeholders ◽  
Robot Interaction ◽  
Improve Design ◽  
Assistive Robots ◽  
Interaction Research

Objective We reviewed human–robot interaction (HRI) participatory design (PD) research with older adults. The goal was to identify methods used, determine their value for design of robots with older adults, and provide guidance for best practices. Background Assistive robots may promote aging-in-place and quality of life for older adults. However, the robots must be designed to meet older adults’ specific needs and preferences. PD and other user-centered methods may be used to engage older adults in the robot development process to accommodate their needs and preferences and to assure usability of emergent assistive robots. Method This targeted review of HRI PD studies with older adults draws on a detailed review of 26 articles. Our assessment focused on the HRI methods and their utility for use with older adults who have a range of needs and capabilities. Results Our review highlighted the importance of using mixed methods and including multiple stakeholders throughout the design process. These approaches can encourage mutual learning (to improve design by developers and to increase acceptance by users). We identified key phases used in HRI PD workshops (e.g., initial interview phase, series of focus groups phase, and presentation phase). These approaches can provide inspiration for future efforts. Conclusion HRI PD strategies can support designers in developing assistive robots that meet older adults’ needs, capabilities, and preferences to promote acceptance. More HRI research is needed to understand potential implications for aging-in-place. PD methods provide a promising approach.

Design of the Human-Robot Interaction for a Semi-Autonomous Service Robot to Assist Elderly People

2015 ◽  
pp. 15-29 ◽  
Author(s):  
Marcus Mast ◽  
Michael Burmester ◽  
Birgit Graf ◽  
Florian Weisshardt ◽  
Georg Arbeiter ◽  
...  
Keyword(s):  
Elderly People ◽  
Human Robot Interaction ◽  
Service Robot ◽  
Robot Interaction ◽  
Autonomous Service

scholarly journals Jealousy 4.0? An empirical study on jealousy-related discomfort of women evoked by other women and gynoid robots

2018 ◽  
Vol 9 (1) ◽  
pp. 323-336 ◽  
Author(s):  
Jessica M. Szczuka ◽  
Nicole C. Krämer
Keyword(s):  
Empirical Study ◽  
Sexual Intercourse ◽  
Physical Attractiveness ◽  
Empirical Studies ◽  
Negative Attitude ◽  
Personal Characteristics ◽  
Self Esteem ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Online Study

Abstract While first empirical studies on sexual aspects of human-robot interaction mostly focus on male users’ acceptance, there is no empirical research on how females react to robotic replications of women. To empirically investigate whether robots can evoke the same kind of jealousy-related discomfort as do other women, we conducted an online study in which 848 heterosexual female participants from Germany reacted to the idea that their partner had sexual intercourse with either another woman, a human-like female-looking robot, or a machinelike female-looking robot. The results revealed dimensions in which the jealousy-related discomfort was higher for female competitors compared to the robotic ones (e.g., discomfort caused by the idea of sexual intercourse),whereas in others the robots evoked the same or higher levels of jealousy-related discomfort (e.g., discomfort caused by feelings of inadequacy, discomfort caused by shared emotional and time resources). The variance in the discomfort regarding sexual interactions between one’s partner and robotic competitors could not be explained by personal characteristics (such as self-esteem, subjective physical attractiveness) but rather by technology-related variables (e.g., negative attitude towards robots, a tendency towards anthropomorphism) and the attitude towards sexual nonexclusivity in relationships. The study provides first empirical insights into a question which is of relevance for a responsible handling of sexualized technologies.

scholarly journals Gentle Versus Strong Touch Classification: Preliminary Results, Challenges, and Potentials

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3033
Author(s):  
Soheil Keshmiri ◽  
Masahiro Shiomi ◽  
Hidenobu Sumioka ◽  
Takashi Minato ◽  
Hiroshi Ishiguro
Keyword(s):  
Preliminary Investigation ◽  
Real Life ◽  
Human Robot Interaction ◽  
Machine Learning Algorithms ◽  
Robot Interaction ◽  
Affective Communication ◽  
Assistive Robots ◽  
Socially Assistive Robots ◽  
Average Accuracy ◽  
Different Types

Touch plays a crucial role in humans’ nonverbal social and affective communication. It then comes as no surprise to observe a considerable effort that has been placed on devising methodologies for automated touch classification. For instance, such an ability allows for the use of smart touch sensors in such real-life application domains as socially-assistive robots and embodied telecommunication. In fact, touch classification literature represents an undeniably progressive result. However, these results are limited in two important ways. First, they are mostly based on overall (i.e., average) accuracy of different classifiers. As a result, they fall short in providing an insight on performance of these approaches as per different types of touch. Second, they do not consider the same type of touch with different level of strength (e.g., gentle versus strong touch). This is certainly an important factor that deserves investigating since the intensity of a touch can utterly transform its meaning (e.g., from an affectionate gesture to a sign of punishment). The current study provides a preliminary investigation of these shortcomings by considering the accuracy of a number of classifiers for both, within- (i.e., same type of touch with differing strengths) and between-touch (i.e., different types of touch) classifications. Our results help verify the strength and shortcoming of different machine learning algorithms for touch classification. They also highlight some of the challenges whose solution concepts can pave the path for integration of touch sensors in such application domains as human–robot interaction (HRI).

Sign in / Sign up

Export Citation Format

Share Document