Dancing with Giants: Learning Goal-Directed Non-Verbal Attunement with Large-Scale Inflatable Robots
2026. Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems.
This research investigates non-verbal, embodied interaction with unfamiliar agents, focusing on large-scale soft robotic systems and their potential to support learning, coordination, and self-reflection. Inspired by equine-assisted interventions (EAIs), therapeutic practices with live horses that foster emotional regulation and wellbeing, it examines interaction as a relational process shaped by ambiguity, resistance, and reciprocal responsiveness. Across autoethnography, co-design, and interaction studies, it explores how attunement emerges through breakdown, repair, and embodied negotiation. Soft, inflatable robots provide a material platform that combines physical safety with human-scale presence, enabling exploration of autonomy, uncertainty, and embodied risk. Rather than replacing EAIs, this work investigates how relational mechanisms can be translated into robotic systems to support reflective awareness of bodily behaviour, coordination, and co-regulation. It contributes to HCI and HRI by challenging comfort-oriented design paradigms and positioning robots as relational partners shaping interaction through calibrated unpredictability and reciprocal embodiment.
Full paper
https://dl.acm.org/doi/full/10.1145/3772363.3799216
Citation
Weir, E. (2026). Dancing with giants: learning goal-directed non-verbal attunement with large-scale inflatable robots. Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1–4).
BibTeX
@inproceedings{weir2026dancing, title={Dancing with Giants: Learning Goal-Directed Non-Verbal Attunement with Large-Scale Inflatable Robots}, author={Weir, Ellen}, booktitle={Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems}, pages={1--4}, year={2026} }