MINI REVIEW article
Front. Comput. Sci.
Sec. Human-Media Interaction
Volume 7 - 2025 | doi: 10.3389/fcomp.2025.1575667
This article is part of the Research TopicEmbodied Perspectives on Sound and Music AIView all 3 articles
How can we make robot dance expressive and responsive? A survey of methods and future directions
Provisionally accepted- 1University of Oslo, Oslo, Norway
- 2Simula Metropolitan Center for Digital Engineering, Oslo, Norway
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The development of robots that can dance like humans presents a complex challenge due to the disparate abilities involved and various aesthetic qualities that need to be achieved. This article reviews recent advances in robotics, artificial intelligence, and human-robot interaction towards enabling various aspects of realistic dance, and examines potential paths towards a fully embodied dancing agent. We begin by outlining the essential abilities required for a robot to perform human-like dance movements and the resulting aesthetic qualities, summarized under the terms expressiveness and responsiveness. Subsequently, we present a review of the current state-of-the-art in dance-related robot technology, highlighting notable achievements, limitations and trade-offs in existing systems. Our analysis covers various approaches, including traditional control systems, machine learning algorithms, and hybrid systems that aim to imbue robots with the capacity for responsive, expressive movement. Finally, we identify and discuss the critical gaps in current research and technology that need to be addressed for the full realization of realistic dancing robots. These include challenges in real-time motion planning, adaptive learning from human dancers, and morphology independence. By mapping out current methods and challenges, we aim to provide insights that may guide future innovations in creating more engaging, responsive, and expressive robotic systems.
Keywords: dance, human-robot interaction, Expressive movement, Sensory feedback, Generative AI, robot control
Received: 12 Feb 2025; Accepted: 15 May 2025.
Copyright: © 2025 Wallace, Glette and Szorkovszky. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Benedikte Wallace, University of Oslo, Oslo, Norway
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