| 1. |
- Billing, Erik, PhD, 1981-, et al.
(författare)
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The DREAM Dataset : Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy
- 2020
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Ingår i: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 15:8
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Tidskriftsartikel (refereegranskat)abstract
- We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and more than 300 hours of therapy. Half of the children interacted with the social robot NAO supervised by a therapist. The other half, constituting a control group, interacted directly with a therapist. Both groups followed the Applied Behavior Analysis (ABA) protocol. Each session was recorded with three RGB cameras and two RGBD (Kinect) cameras, providing detailed information of children’s behavior during therapy. This public release of the dataset comprises body motion, head position and orientation, and eye gaze variables, all specified as 3D data in a joint frame of reference. In addition, metadata including participant age, gender, and autism diagnosis (ADOS) variables are included. We release this data with the hope of supporting further data-driven studies towards improved therapy methods as well as a better understanding of ASD in general.
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| 2. |
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| 3. |
- Esteban, Pablo G., et al.
(författare)
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How to Build a Supervised Autonomous System for Robot-Enhanced Therapy for Children with Autism Spectrum Disorder
- 2017
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Ingår i: Paladyn - Journal of Behavioral Robotics. - : De Gruyter Open. - 2080-9778 .- 2081-4836. ; 8:1, s. 18-38
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Tidskriftsartikel (refereegranskat)abstract
- Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.
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| 4. |
- Hernández García, Daniel, et al.
(författare)
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Social Robots in Therapy and Care
- 2019
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Ingår i: Proceedings of the 14th ACM/IEEE International Conference on Human Robot Interaction. - Daegu : IEEE conference proceedings. - 9781538685556 - 9781538685563 - 9781538685549 ; , s. 669-670
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Konferensbidrag (refereegranskat)abstract
- The Social Robots in Therapy workshop series aims at advancing research topics related to the use of robots in the contexts of Social Care and Robot-Assisted Therapy (RAT). Robots in social care and therapy have been a long time promise in HRI as they have the opportunity to improve patients life significantly. Multiple challenges have to be addressed for this, such as building platforms that work in proximity with patients, therapists and health-care professionals; understanding user needs; developing adaptive and autonomous robot interactions; and addressing ethical questions regarding the use of robots with a vulnerable population. The full-day workshop follows last year's edition which centered on how social robots can improve health-care interventions, how increasing the degree of autonomy of the robots might affect therapies, and how to overcome the ethical challenges inherent to the use of robot assisted technologies. This 2nd edition of the workshop will be focused on the importance of equipping social robots with socio-emotional intelligence and the ability to perform meaningful and personalized interactions. This workshop aims to bring together researchers and industry experts in the fields of Human-Robot Interaction, Machine Learning and Robots in Health and Social Care. It will be an opportunity for all to share and discuss ideas, strategies and findings to guide the design and development of robot assisted systems for therapy and social care implementations that can provide personalize, natural, engaging and autonomous interactions with patients (and health-care providers).
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| 5. |
- Senft, Emmanuel, et al.
(författare)
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Participatory Design and End-User Programming for Human-Robot Interaction
- 2022
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Ingår i: PROCEEDINGS OF THE 2022 17TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI '22). - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 1290-1292
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Konferensbidrag (refereegranskat)abstract
- The Participatory Design and End-User Programming for Human-Robot Interaction (HRI) workshop aims to advance research on how to design systems that can be used by end users to program robots. There tends to be a fracture in HRI between the technical designers of robot programs (often engineers or computer scientists) and the actual users of such robots. Developers have the capabilities to program robots but often lack insights possessed by domain experts, sometimes leading to technically interesting but impractical systems. With this workshop, we aim to bridge two different methods often used individually within the wider HRI community to involve end users in robot program design: Participatory Design (PD) and End-User Programming (EUP). Both methods empower end users to co-produce robots addressing real-world needs. However, there have been limited opportunities to unite researchers who specialize in these areas and engage in mutual learning. We will address this shortcoming with a full-day workshop, which will put the PD and EUP communities in touch, inviting speakers from both sides and welcoming a wide range of publications from describing new end-user programming methods to compiling insights learned from conducting participatory design studies.
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| 6. |
- Winkle, Katie, et al.
(författare)
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LEADOR : A Method for End-To-End Participatory Design of Autonomous Social Robots
- 2021
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Ingår i: Frontiers in Robotics and AI. - : Frontiers Media SA. - 2296-9144. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Participatory design (PD) has been used to good success in human-robot interaction (HRI) but typically remains limited to the early phases of development, with subsequent robot behaviours then being hardcoded by engineers or utilised in Wizard-of-Oz (WoZ) systems that rarely achieve autonomy. In this article, we present LEADOR (Led-by-Experts Automation and Design Of Robots), an end-to-end PD methodology for domain expert co-design, automation, and evaluation of social robot behaviour. This method starts with typical PD, working with the domain expert(s) to co-design the interaction specifications and state and action space of the robot. It then replaces the traditional offline programming or WoZ phase by an in situ and online teaching phase where the domain expert can live-program or teach the robot how to behave whilst being embedded in the interaction context. We point out that this live teaching phase can be best achieved by adding a learning component to a WoZ setup, which captures implicit knowledge of experts, as they intuitively respond to the dynamics of the situation. The robot then progressively learns an appropriate, expert-approved policy, ultimately leading to full autonomy, even in sensitive and/or ill-defined environments. However, LEADOR is agnostic to the exact technical approach used to facilitate this learning process. The extensive inclusion of the domain expert(s) in robot design represents established responsible innovation practice, lending credibility to the system both during the teaching phase and when operating autonomously. The combination of this expert inclusion with the focus on in situ development also means that LEADOR supports a mutual shaping approach to social robotics. We draw on two previously published, foundational works from which this (generalisable) methodology has been derived to demonstrate the feasibility and worth of this approach, provide concrete examples in its application, and identify limitations and opportunities when applying this framework in new environments.
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