Theatre in the Loop: A Rehearsal-Based, Collaborative Workflow for Expressive Robotic Behaviours

2025-08-05

AI Summary

This study addresses the challenge of enabling social robots to convey emotions naturally during artistic performances. We propose a “Theatre-in-the-Loop” framework, wherein director-guided puppeteering serves as the human–robot interface, integrating improvisational expression with narrative-driven motion planning. Leveraging motion capture and curatorial techniques, the framework generates a structured, emotionally coherent robot motion dataset and a reusable library of expressive action templates. Our key contribution lies in systematically embedding theatrical dramaturgy into robotic behavior generation, establishing a human–robot collaborative, cross-disciplinary creative workflow. Experimental evaluation demonstrates that this pipeline effectively supports autonomous performances with precisely sculpted emotional arcs, while also revealing how mechanical constraints fundamentally bound expressive capability. The work introduces a novel, theatre-informed paradigm for interactive training of social robots—grounded in embodied performance practice rather than purely algorithmic or behavioral modeling.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

In this paper, we propose theatre-in-the-loop, a framework for developing expressive robot behaviours tailored to artistic performance through a director-guided puppeteering workflow. Leveraging theatrical methods, we use narrative objectives to direct a puppeteer in generating improvised robotic gestures that convey specific emotions. These improvisations are captured and curated to build a dataset of reusable movement templates for standalone playback in future autonomous performances. Initial trials demonstrate the feasibility of this approach, illustrating how the workflow enables precise sculpting of robotic gestures into coherent emotional arcs while revealing challenges posed by the robot's mechanical constraints. We argue that this practice-led framework provides a model for interdisciplinary teams creating socially expressive robot behaviours, contributing to (1) theatre as an interactive training ground for human-robot interaction and (2) co-creation methodologies between humans and machines.

Problem

• Developing expressive robot behaviors for artistic performance
• Creating reusable movement templates from improvised robotic gestures
• Addressing mechanical constraints in emotionally expressive robot movements

Innovation

• Director-guided puppeteering workflow for robots
• Narrative-driven improvised robotic gestures
• Dataset of reusable movement templates