Mood Dynamics: Integrating Emotional Expressiveness into Robotic Task Execution
This paper introduces Mood Dynamics, a framework for generating emotive emergent behaviors in robotic task completion by extending Laban's unpublished model of Effort-Shape with modern computational tools. The framework integrates a dynamic Line of Axis <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$L(t)$</tex>, which ensures stability and alignment, with Effort <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$E(t)$</tex>, capturing the emotive and behavioral qualities of movement. By implementing a GAN-RL architecture and probabilistic sampling, Mood Dynamics enables robots to adapt their trajectories in real-time, conveying emotion while executing tasks. The core rules of Mood Dynamics, including Inclination and Attunement, are defined as computational formulations, providing a foundation for future research in task-oriented expressive robotic systems.
Authors
- N Miya Sylvester
Institutions
- Carnegie Mellon University (US)
Publication Details
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/hri61500.2025.10973860
- Primary Topic
- Reinforcement Learning in Robotics
- Type
- article
- Field-Weighted Citation Impact
- 0.00