Designing Social Robots for Social-Cognition Training with Autistic Adults
- URL: http://arxiv.org/abs/2608.18488v1
- Date: Wed, 19 Aug 2026 03:25:17 GMT
- Title: Designing Social Robots for Social-Cognition Training with Autistic Adults
- Abstract summary: We conducted an online focus group and co-design session with five autistic adults to explore what a social robot for social-cognition training should do.<n>The resulting verbal and visual data were analysed using reflexive thematic analysis.<n>The analysis yielded seven themes that define core design requirements.
- Score: 0.7820502905172284
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Social robots have been widely explored as tools for autism intervention, yet this literature has focused predominantly on children and has rarely involved autistic adults as active contributors to design. This creates a mismatch between existing systems and the social-cognitive challenges autistic adults actually face in everyday life, including navigating ambiguous interpersonal contexts, managing conversational timing, and interpreting implied emotional meaning. To address this gap, we conducted an online focus group and co-design session with five autistic adults to explore what a social robot for social-cognition training should do, how it should interact, and under what conditions it would be genuinely useful. The 90-minute session combined open discussion with structured co-design activities on a shared digital whiteboard, and the resulting verbal and visual data were analysed using reflexive thematic analysis. The analysis yielded seven themes that define core design requirements: the robot should function as a scaffold rather than a substitute, prioritise authenticity over comfort, provide personalised and user-controlled feedback, accommodate emotional self-awareness gaps, respect privacy and contextual boundaries, support rehearsal for real-world social situations, and remain configurable in identity, form, and expression. Together, the findings suggest that autistic adults envision the robot not as a companion or live social assistant, but as a private, configurable rehearsal partner designed to support independence over time.
Related papers
- Perception of Social Robots as Communication Partners in Healthcare for Older Adults [0.9172009366241242]
This study addresses whether social robots can serve as effective interaction partners compared to humans, and if "positive prompts" can similarly enhance these interactions.<n>Our multi-modal analysis, integrating facial expression data, heart rate variability, and subjective questionnaires, revealed no significant differences in overall stress levels between human and robot interactions.
arXiv Detail & Related papers (2026-05-20T11:38:45Z) - Human vs. NAO: A Computational-Behavioral Framework for Quantifying Social Orienting in Autism and Typical Development [0.6999740786886536]
Responding to one's name is one of the most prominent aspects in the detection of Autism Spectrum Disorder (ASD)<n>Children with ASD often demonstrate reduced frequency, increased latency or atypical patterns of response.<n>This work aims to understand how the source and modality of social cues affect attentional dynamics in name-calling contexts.
arXiv Detail & Related papers (2026-03-24T03:37:28Z) - Developing Social Robots with Empathetic Non-Verbal Cues Using Large
Language Models [2.5489046505746704]
We design and label four types of empathetic non-verbal cues, abbreviated as SAFE: Speech, Action (gesture), Facial expression, and Emotion, in a social robot.
Preliminary results show distinct patterns in the robot's responses, such as a preference for calm and positive social emotions like 'joy' and 'lively', and frequent nodding gestures.
Our work lays the groundwork for future studies on human-robot interactions, emphasizing the essential role of both verbal and non-verbal cues in creating social and empathetic robots.
arXiv Detail & Related papers (2023-08-31T08:20:04Z) - Proceeding of the 1st Workshop on Social Robots Personalisation At the
crossroads between engineering and humanities (CONCATENATE) [37.838596863193565]
This workshop aims to raise an interdisciplinary discussion on personalisation in robotics.
It aims at bringing researchers from different fields together to propose guidelines for personalisation.
arXiv Detail & Related papers (2023-07-10T11:11:24Z) - Social Assistive Robotics for Autistic Children [56.524774292536264]
The goal of the project is testing autistic children's interactions with the social robot NAO.
The innovative aspect of the project is that the children robot interaction will consider the children's emotions and specific features.
arXiv Detail & Related papers (2022-09-25T18:28:19Z) - Co-Located Human-Human Interaction Analysis using Nonverbal Cues: A
Survey [71.43956423427397]
We aim to identify the nonverbal cues and computational methodologies resulting in effective performance.
This survey differs from its counterparts by involving the widest spectrum of social phenomena and interaction settings.
Some major observations are: the most often used nonverbal cue, computational method, interaction environment, and sensing approach are speaking activity, support vector machines, and meetings composed of 3-4 persons equipped with microphones and cameras, respectively.
arXiv Detail & Related papers (2022-07-20T13:37:57Z) - Symbiotic Child Emotional Support with Social Robots and Temporal
Knowledge Graphs [0.0]
We suggest the development of a symbiotic framework for real-time Emotional Support (ES) with social robots Knowledge Graphs (KG)
The framework both guides the social robot in providing ES statements to the child and assists the expert in tracking and interpreting the child's emotional state and related events over time.
arXiv Detail & Related papers (2022-05-26T08:44:31Z) - Data-driven emotional body language generation for social robotics [58.88028813371423]
In social robotics, endowing humanoid robots with the ability to generate bodily expressions of affect can improve human-robot interaction and collaboration.
We implement a deep learning data-driven framework that learns from a few hand-designed robotic bodily expressions.
The evaluation study found that the anthropomorphism and animacy of the generated expressions are not perceived differently from the hand-designed ones.
arXiv Detail & Related papers (2022-05-02T09:21:39Z) - Cognitive architecture aided by working-memory for self-supervised
multi-modal humans recognition [54.749127627191655]
The ability to recognize human partners is an important social skill to build personalized and long-term human-robot interactions.
Deep learning networks have achieved state-of-the-art results and demonstrated to be suitable tools to address such a task.
One solution is to make robots learn from their first-hand sensory data with self-supervision.
arXiv Detail & Related papers (2021-03-16T13:50:24Z) - Disambiguating Affective Stimulus Associations for Robot Perception and
Dialogue [67.89143112645556]
We provide a NICO robot with the ability to learn the associations between a perceived auditory stimulus and an emotional expression.
NICO is able to do this for both individual subjects and specific stimuli, with the aid of an emotion-driven dialogue system.
The robot is then able to use this information to determine a subject's enjoyment of perceived auditory stimuli in a real HRI scenario.
arXiv Detail & Related papers (2021-03-05T20:55:48Z) - Designing Personalized Interaction of a Socially Assistive Robot for
Stroke Rehabilitation Therapy [64.52563354823711]
The research of a socially assistive robot has a potential to augment and assist physical therapy sessions for patients with neurological and musculoskeletal problems.
This paper presents an interactive approach of a socially assistive robot that can dynamically select kinematic features of assessment on individual patient's exercises to predict the quality of motion.
arXiv Detail & Related papers (2020-07-13T16:12:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.