| 1. |
- Akalin, Neziha, 1988-, et al.
(author)
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A Taxonomy of Factors Influencing Perceived Safety in Human–Robot Interaction
- 2023
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In: International Journal of Social Robotics. - : Springer Science and Business Media B.V.. - 1875-4791 .- 1875-4805.
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Journal article (peer-reviewed)abstract
- Safety is a fundamental prerequisite that must be addressed before any interaction of robots with humans. Safety has been generally understood and studied as the physical safety of robots in human–robot interaction, whereas how humans perceive these robots has received less attention. Physical safety is a necessary condition for safe human–robot interaction. However, it is not a sufficient condition. A robot that is safe by hardware and software design can still be perceived as unsafe. This article focuses on perceived safety in human–robot interaction. We identified six factors that are closely related to perceived safety based on the literature and the insights obtained from our user studies. The identified factors are the context of robot use, comfort, experience and familiarity with robots, trust, the sense of control over the interaction, and transparent and predictable robot actions. We then made a literature review to identify the robot-related factors that influence perceived safety. Based the literature, we propose a taxonomy which includes human-related and robot-related factors. These factors can help researchers to quantify perceived safety of humans during their interactions with robots. The quantification of perceived safety can yield computational models that would allow mitigating psychological harm.
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| 2. |
- Akalin, Neziha, 1988-, et al.
(author)
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An Evaluation Tool of the Effect of Robots in Eldercare on the Sense of Safety and Security
- 2017
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In: Social Robotics. - Cham : Springer International Publishing. - 9783319700229 - 9783319700212 ; , s. 628-637
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Conference paper (peer-reviewed)abstract
- The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency.
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| 3. |
- Akalin, Neziha, 1988-, et al.
(author)
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Enhancing Social Human-Robot Interaction with Deep Reinforcement Learning.
- 2018
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In: Proc. FAIM/ISCA Workshop on Artificial Intelligence for Multimodal Human Robot Interaction, 2018. - : MHRI. ; , s. 48-50
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Conference paper (peer-reviewed)abstract
- This research aims to develop an autonomous social robot for elderly individuals. The robot will learn from the interaction and change its behaviors in order to enhance the interaction and improve the user experience. For this purpose, we aim to use Deep Reinforcement Learning. The robot will observe the user’s verbal and nonverbal social cues by using its camera and microphone, the reward will be positive valence and engagement of the user.
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| 4. |
- Akalin, Neziha, 1988-, et al.
(author)
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The Relevance of Social Cues in Assistive Training with a Social Robot
- 2018
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In: 10th International Conference on Social Robotics, ICSR 2018, Proceedings. - Cham : Springer. - 9783030052034 - 9783030052041 ; , s. 462-471
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Conference paper (peer-reviewed)abstract
- This paper examines whether social cues, such as facial expressions, can be used to adapt and tailor a robot-assisted training in order to maximize performance and comfort. Specifically, this paper serves as a basis in determining whether key facial signals, including emotions and facial actions, are common among participants during a physical and cognitive training scenario. In the experiment, participants performed basic arm exercises with a social robot as a guide. We extracted facial features from video recordings of participants and applied a recursive feature elimination algorithm to select a subset of discriminating facial features. These features are correlated with the performance of the user and the level of difficulty of the exercises. The long-term aim of this work, building upon the work presented here, is to develop an algorithm that can eventually be used in robot-assisted training to allow a robot to tailor a training program based on the physical capabilities as well as the social cues of the users.
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| 5. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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An ontology-based context-aware system for smart homes : E-care@home
- 2017
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In: Sensors. - Basel : MDPI AG. - 1424-8220. ; 17:7
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Journal article (peer-reviewed)abstract
- Smart home environments have a significant potential to provide for long-term monitoring of users with special needs in order to promote the possibility to age at home. Such environments are typically equipped with a number of heterogeneous sensors that monitor both health and environmental parameters. This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. We focus on integrating measurements gathered from heterogeneous sources by using ontologies in order to enable semantic interpretation of events and context awareness. Activities are deduced using an incremental answer set solver for stream reasoning. The paper demonstrates the proposed framework using an instantiation of a smart environment that is able to perform context recognition based on the activities and the events occurring in the home.
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| 6. |
- Coradeschi, Silvia, 1968-, et al.
(author)
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Social robotic telepresence
- 2011
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In: the 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2011).HRI. - New York, NY, USA : ACM Digital Library. - 9781450305617 ; , s. 5-6
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Conference paper (peer-reviewed)
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| 7. |
- Herring, Susan C., et al.
(author)
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The Future of Robotic Telepresence : Visions, Opportunities and Challenges
- 2016
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In: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. - New York : Association for Computing Machinery (ACM). - 9781450340823 ; , s. 1038-1042
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Conference paper (peer-reviewed)abstract
- This panel will bring together experts on robotic telepresence from HCI and related fields. Panelists will engage the audience in a discussion of visions, opportunities and challenges for the future of telepresence robots.
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| 8. |
- Kiselev, Andrey, 1982-, et al.
(author)
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Auditory immersion with stereo sound in a mobile robotic telepresence system
- 2015
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In: 10th ACM/IEEE International Conference on Human-Robot Interaction, 2015. - : Association for Computing Machinery (ACM).
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Conference paper (peer-reviewed)abstract
- Auditory immersion plays a significant role in generating a good feeling of presence for users driving a telepresence robot. In this paper, one of the key characteristics of auditory immersion - sound source localization (SSL) - is studied from the perspective of those who operate telepresence robots from remote locations. A prototype which is capable of delivering soundscape to the user through Interaural Time Difference (ITD) and Interaural Level Difference (ILD) using the ORTF stereo recording technique was developed. The prototype was evaluated in an experiment and the results suggest that the developed method is sufficient for sound source localization tasks.
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| 9. |
- Kiselev, Andrey, 1982-, et al.
(author)
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Combining Semi-autonomous Navigation with Manned Behaviour in a Cooperative Driving System for Mobile Robotic Telepresence
- 2015
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In: COMPUTER VISION - ECCV 2014 WORKSHOPS, PT IV. - Berlin : Springer Berlin/Heidelberg. - 9783319162201 - 9783319162195 ; , s. 17-28
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Conference paper (peer-reviewed)abstract
- This paper presents an image-based cooperative driving system for telepresence robot, which allows safe operation in indoor environments and is meant to minimize the burden on novice users operating the robot. The paper focuses on one emerging telepresence robot, namely, mobile remote presence systems for social interaction. Such systems brings new opportunities for applications in healthcare and elderly care by allowing caregivers to communicate with patients and elderly from remote locations. However, using such systems can be a difficult task particularly for caregivers without proper training. The paper presents a first implementation of a vision-based cooperative driving enhancement to a telepresence robot. A preliminary evaluation in the laboratory environment is presented.
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| 10. |
- Kiselev, Andrey, 1982-, et al.
(author)
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Evaluation of using semi-autonomy features in mobile robotic telepresence systems
- 2015
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In: Proceedings of the 2015 7th IEEE International Conference on Cybernetics and Intelligent Systems, CIS 2015 and Robotics, Automation and Mechatronics, RAM 2015. - New York, USA : IEEE conference proceedings. - 9781467373388 ; , s. 147-152
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Conference paper (peer-reviewed)abstract
- Mobile robotic telepresence systems used for social interaction scenarios require that users steer robots in a remote environment. As a consequence, a heavy workload can be put on users if they are unfamiliar with using robotic telepresence units. One way to lessen this workload is to automate certain operations performed during a telepresence session in order to assist remote drivers in navigating the robot in new environments. Such operations include autonomous robot localization and navigation to certain points in the home and automatic docking of the robot to the charging station. In this paper we describe the implementation of such autonomous features along with user evaluation study. The evaluation scenario is focused on the first experience on using the system by novice users. Importantly, that the scenario taken in this study assumed that participants have as little as possible prior information about the system. Four different use-cases were identified from the user behaviour analysis.
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