How can we make robot dance expressive and responsive? A survey of methods and future directions
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 toward enabling v...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Computer Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcomp.2025.1575667/full |
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| _version_ | 1849696564699725824 |
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| author | Benedikte Wallace Benedikte Wallace Kyrre Glette Kyrre Glette Alex Szorkovszky |
| author_facet | Benedikte Wallace Benedikte Wallace Kyrre Glette Kyrre Glette Alex Szorkovszky |
| author_sort | Benedikte Wallace |
| collection | DOAJ |
| description | 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 toward enabling various aspects of realistic dance, and examines potential paths toward 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. |
| format | Article |
| id | doaj-art-44eebb0d221b44d09c72c3fd88952db5 |
| institution | DOAJ |
| issn | 2624-9898 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computer Science |
| spelling | doaj-art-44eebb0d221b44d09c72c3fd88952db52025-08-20T03:19:25ZengFrontiers Media S.A.Frontiers in Computer Science2624-98982025-06-01710.3389/fcomp.2025.15756671575667How can we make robot dance expressive and responsive? A survey of methods and future directionsBenedikte Wallace0Benedikte Wallace1Kyrre Glette2Kyrre Glette3Alex Szorkovszky4RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, NorwayDepartment of Informatics, University of Oslo, Oslo, NorwayRITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, NorwayDepartment of Informatics, University of Oslo, Oslo, NorwayDepartment of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, NorwayThe 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 toward enabling various aspects of realistic dance, and examines potential paths toward 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.https://www.frontiersin.org/articles/10.3389/fcomp.2025.1575667/fulldancehuman-robot interactionexpressive movementsensory feedbackgenerative AIrobot control |
| spellingShingle | Benedikte Wallace Benedikte Wallace Kyrre Glette Kyrre Glette Alex Szorkovszky How can we make robot dance expressive and responsive? A survey of methods and future directions Frontiers in Computer Science dance human-robot interaction expressive movement sensory feedback generative AI robot control |
| title | How can we make robot dance expressive and responsive? A survey of methods and future directions |
| title_full | How can we make robot dance expressive and responsive? A survey of methods and future directions |
| title_fullStr | How can we make robot dance expressive and responsive? A survey of methods and future directions |
| title_full_unstemmed | How can we make robot dance expressive and responsive? A survey of methods and future directions |
| title_short | How can we make robot dance expressive and responsive? A survey of methods and future directions |
| title_sort | how can we make robot dance expressive and responsive a survey of methods and future directions |
| topic | dance human-robot interaction expressive movement sensory feedback generative AI robot control |
| url | https://www.frontiersin.org/articles/10.3389/fcomp.2025.1575667/full |
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