2,189 research outputs found
Tactile Interactions with a Humanoid Robot : Novel Play Scenario Implementations with Children with Autism
Acknowledgments: This work has been partially supported by the European Commission under contract number FP7-231500-ROBOSKIN. Open Access: This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.The work presented in this paper was part of our investigation in the ROBOSKIN project. The project has developed new robot capabilities based on the tactile feedback provided by novel robotic skin, with the aim to provide cognitive mechanisms to improve human-robot interaction capabilities. This article presents two novel tactile play scenarios developed for robot-assisted play for children with autism. The play scenarios were developed against specific educational and therapeutic objectives that were discussed with teachers and therapists. These objectives were classified with reference to the ICF-CY, the International Classification of Functioning – version for Children and Youth. The article presents a detailed description of the play scenarios, and case study examples of their implementation in HRI studies with children with autism and the humanoid robot KASPAR.Peer reviewedFinal Published versio
Robust Modeling of Epistemic Mental States
This work identifies and advances some research challenges in the analysis of
facial features and their temporal dynamics with epistemic mental states in
dyadic conversations. Epistemic states are: Agreement, Concentration,
Thoughtful, Certain, and Interest. In this paper, we perform a number of
statistical analyses and simulations to identify the relationship between
facial features and epistemic states. Non-linear relations are found to be more
prevalent, while temporal features derived from original facial features have
demonstrated a strong correlation with intensity changes. Then, we propose a
novel prediction framework that takes facial features and their nonlinear
relation scores as input and predict different epistemic states in videos. The
prediction of epistemic states is boosted when the classification of emotion
changing regions such as rising, falling, or steady-state are incorporated with
the temporal features. The proposed predictive models can predict the epistemic
states with significantly improved accuracy: correlation coefficient (CoERR)
for Agreement is 0.827, for Concentration 0.901, for Thoughtful 0.794, for
Certain 0.854, and for Interest 0.913.Comment: Accepted for Publication in Multimedia Tools and Application, Special
Issue: Socio-Affective Technologie
Requirements for Robotic Interpretation of Social Signals “in the Wild”: Insights from Diagnostic Criteria of Autism Spectrum Disorder
The last few decades have seen widespread advances in technological means to characterise
observable aspects of human behaviour such as gaze or posture. Among others, these developments
have also led to significant advances in social robotics. At the same time, however, social robots
are still largely evaluated in idealised or laboratory conditions, and it remains unclear whether
the technological progress is sufficient to let such robots move “into the wild”. In this paper, we
characterise the problems that a social robot in the real world may face, and review the technological
state of the art in terms of addressing these. We do this by considering what it would entail
to automate the diagnosis of Autism Spectrum Disorder (ASD). Just as for social robotics, ASD
diagnosis fundamentally requires the ability to characterise human behaviour from observable
aspects. However, therapists provide clear criteria regarding what to look for. As such, ASD diagnosis
is a situation that is both relevant to real-world social robotics and comes with clear metrics. Overall,
we demonstrate that even with relatively clear therapist-provided criteria and current technological
progress, the need to interpret covert behaviour cannot yet be fully addressed. Our discussions have
clear implications for ASD diagnosis, but also for social robotics more generally. For ASD diagnosis,
we provide a classification of criteria based on whether or not they depend on covert information
and highlight present-day possibilities for supporting therapists in diagnosis through technological
means. For social robotics, we highlight the fundamental role of covert behaviour, show that the
current state-of-the-art is unable to characterise this, and emphasise that future research should tackle
this explicitly in realistic settings
What makes a social robot good at interacting with humans?
This paper discusses the nuances of a social robot, how and why social robots are becoming increasingly significant, and what they are currently being used for. This paper also reflects on the current design of social robots as a means of interaction with humans and also reports potential solutions about several important questions around the futuristic design of these robots. The specific questions explored in this paper are: “Do social robots need to look like living creatures that already exist in the world for humans to interact well with them?”; “Do social robots need to have animated faces for humans to interact well with them?”; “Do social robots need to have the ability to speak a coherent human language for humans to interact well with them?” and “Do social robots need to have the capability to make physical gestures for humans to interact well with them?”. This paper reviews both verbal as well as nonverbal social and conversational cues that could be incorporated into the design of social robots, and also briefly discusses the emotional bonds that may be built between humans and robots. Facets surrounding acceptance of social robots by humans and also ethical/moral concerns have also been discussed
What makes a social robot good at interacting with humans?
This paper discusses the nuances of a social robot, how and why social robots are becoming increasingly significant, and what they are currently being used for. This paper also reflects on the current design of social robots as a means of interaction with humans and also reports potential solutions about several important questions around the futuristic design of these robots. The specific questions explored in this paper are: “Do social robots need to look like living creatures that already exist in the world for humans to interact well with them?”; “Do social robots need to have animated faces for humans to interact well with them?”; “Do social robots need to have the ability to speak a coherent human language for humans to interact well with them?” and “Do social robots need to have the capability to make physical gestures for humans to interact well with them?”. This paper reviews both verbal as well as nonverbal social and conversational cues that could be incorporated into the design of social robots, and also briefly discusses the emotional bonds that may be built between humans and robots. Facets surrounding acceptance of social robots by humans and also ethical/moral concerns have also been discussed
Adaptable videogame platform for interactive upper extremity rehabilitation
The primary objective of this work is to design a recreational rehabilitation videogame platform for customizing motivating games that interactively encourage purposeful upper extremity gross motor movements. Virtual reality (VR) technology is a popular application for rehabilitation therapies but there is a constant need for more accessible and affordable systems. We have developed a recreational VR game platform can be used as an independent therapy supplement without laboratory equipment and is inexpensive, motivating, and adaptable. The behaviors and interactive features can be easily modified and customized based on players\u27 limitations or progress.
A real-time method of capturing hand movements using programmed color detection mechanisms to create the simulated virtual environments (VEs) is implemented. Color markers are tracked and simultaneously given coordinates in the VE where the player sees representations of their hands and other interacting objects whose behaviors can be customized and adapted to fit therapeutic objectives and players\u27 interests. After gross motor task repetition and involvement in the adaptable games, mobility of the upper extremities may improve. The videogame platform is expanded and optimized to allow modifications to base inputs and algorithms for object interactions through graphical user interfaces, thus providing the adaptable need in VR rehabilitation
Analysis of the hands in egocentric vision: A survey
Egocentric vision (a.k.a. first-person vision - FPV) applications have
thrived over the past few years, thanks to the availability of affordable
wearable cameras and large annotated datasets. The position of the wearable
camera (usually mounted on the head) allows recording exactly what the camera
wearers have in front of them, in particular hands and manipulated objects.
This intrinsic advantage enables the study of the hands from multiple
perspectives: localizing hands and their parts within the images; understanding
what actions and activities the hands are involved in; and developing
human-computer interfaces that rely on hand gestures. In this survey, we review
the literature that focuses on the hands using egocentric vision, categorizing
the existing approaches into: localization (where are the hands or parts of
them?); interpretation (what are the hands doing?); and application (e.g.,
systems that used egocentric hand cues for solving a specific problem).
Moreover, a list of the most prominent datasets with hand-based annotations is
provided
Applications of Affective Computing in Human-Robot Interaction: state-of-art and challenges for manufacturing
The introduction of collaborative robots aims to make production more flexible, promoting a greater interaction between humans and robots also from physical point of view. However, working closely with a robot may lead to the creation of stressful situations for the operator, which can negatively affect task performance.
In Human-Robot Interaction (HRI), robots are expected to be socially intelligent, i.e., capable of understanding and reacting accordingly to human social and affective clues. This ability can be exploited implementing affective computing, which concerns the development of systems able to recognize, interpret, process, and simulate human affects. Social intelligence is essential for robots to establish a natural interaction with people in several contexts, including the manufacturing sector with the emergence of Industry 5.0.
In order to take full advantage of the human-robot collaboration, the robotic system should be able to perceive the psycho-emotional and mental state of the operator through different sensing modalities (e.g., facial expressions, body language, voice, or physiological signals) and to adapt its behaviour accordingly. The development of socially intelligent collaborative robots in the manufacturing sector can lead to a symbiotic human-robot collaboration, arising several research challenges that still need to be addressed.
The goals of this paper are the following: (i) providing an overview of affective computing implementation in HRI; (ii) analyzing the state-of-art on this topic in different application contexts (e.g., healthcare, service applications, and manufacturing); (iii) highlighting research challenges for the manufacturing sector
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