GenSwarm: Scalable multi-robot code-policy generation and deployment via language models

Abstract

The development of control policies for multi-robot systems traditionally follows a complex and labor-intensive process, often lacking the flexibility to adapt to dynamic tasks. This has motivated research on methods to automatically create control policies. However, these methods require iterative processes of manually crafting and refining objective functions, thereby prolonging the development cycle. This work introduces GenSwarm, an end-to-end system that leverages large language models to automatically generate and deploy control policies for real-world multi-robot systems based on user instructions in natural language. As a multi-language-agent system, GenSwarm achieves zero-shot learning, enabling rapid adaptation to altered or unseen tasks. The white-box nature of the code policies ensures strong reproducibility and interpretability. With its scalable software and hardware architectures, GenSwarm supports efficient and automated policy deployment on both simulated and real-world multi-robot systems, realizing an instruction-to-execution end-to-end functionality that may transform the development paradigm of multi-robot systems in the future.

Metadata

Item Type:	Article
Authors/Creators:	Ji, W. Chen, H. Chen, M. Zhu, G. Xu, L. Groß, R. https://orcid.org/0000-0003-1826-1375 Zhou, R. Cao, M. Zhao, S.
Copyright, Publisher and Additional Information:	© The Author(s) 2025. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/bync-nd/4.0/.
Keywords:	Engineering; Physics
Dates:	Submitted: 24 February 2025 Accepted: 30 October 2025 Published (online): 9 January 2026 Published: 9 January 2026
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
Funding Information:	Funder Grant number UK RESEARCH AND INNOVATION 10048272 101093046 UK RESEARCH AND INNOVATION / UKRI / RCUK 10048272
Date Deposited:	20 Jan 2026 08:55
Last Modified:	20 Jan 2026 08:55
Status:	Published
Publisher:	Springer Science and Business Media LLC
Refereed:	Yes
Identification Number:	10.1038/s44182-025-00065-w
Related URLs:	Software or Code
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:236721

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GenSwarm: Scalable multi-robot code-policy generation and deployment via language models

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