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Robotic digital twin: a lifecycle perspective from design to application and maintenance – a review AITranslate

Yuxin Sun1; Zhengqing Fu1; Peiyi Li1; Yadong Xu2; Zhenhua Xiong1; Jinchen Ji3;
1.The Meta Robotics Institute and the State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China
2.The Department of Industrial and Systems Engineering, and also with the Research Institute for Advanced Manufacturing, The Hong Kong Polytechnic University, Hong Kong 999077, China
3.The School of Mechanical and Mechatronic Engineering, University of Technology Sydney, NSW 2007, Australia
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Publisher: Youke Publish Co., Ltd.
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Abstract AITranslate

Robotic digital twins are emerging as a transformative paradigm in robotics, enabling real-time synchronization between physical robots and high-fidelity virtual replicas. Compared with traditional simulation, robotic digital twins establish a closed-loop physical–virtual–data–service–knowledge architecture that supports lifecycle management, predictive analysis, and autonomous optimization. This review provides a comprehensive synthesis of recent progress in robotic digital twins. First, we summarize the core architecture and dynamic characteristics, highlighting multi-level multi-domain modeling and real-time bidirectional interaction. Second, we analyze the key technology stack, including data acquisition and fusion, high-fidelity model construction, anomaly prediction, and artificial intelligence (AI)-enhanced decision-making. Third, we examine representative applications in operation and maintenance contexts, personalized service, and human–robot collaboration. Finally, we discuss major challenges, such as model fidelity, synchronization performance, and standardization, and then outline future directions toward artificial intelligence-digital twin (AI-DT) symbiosis, cross-domain system integration, and human-centric ecosystems. This survey aims to serve as a reference for both academic research and industrial deployment of robotic digital twins.

KeyWords AITranslate

AI human-robot collaboration real-time simulation robotic digital twin smart manufacturing

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DOI：10.23919/CHAIN.2026.000004

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Citation Information:

Robotic digital twins are emerging as a transformative paradigm in robotics, enabling real-time synchronization between physical robots and high-fidelity virtual replicas. Compared with traditional simulation, robotic digital twins establish a closed-loop physical–virtual–data–service–knowledge architecture that supports lifecycle management, predictive analysis, and autonomous optimization. This review provides a comprehensive synthesis of recent progress in robotic digital twins. First, we summarize the core architecture and dynamic characteristics, highlighting multi-level multi-domain modeling and real-time bidirectional interaction. Second, we analyze the key technology stack, including data acquisition and fusion, high-fidelity model construction, anomaly prediction, and artificial intelligence (AI)-enhanced decision-making. Third, we examine representative applications in operation and maintenance contexts, personalized service, and human–robot collaboration. Finally, we discuss major challenges, such as model fidelity, synchronization performance, and standardization, and then outline future directions toward artificial intelligence-digital twin (AI-DT) symbiosis, cross-domain system integration, and human-centric ecosystems. This survey aims to serve as a reference for both academic research and industrial deployment of robotic digital twins.

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GB/T 7714-2015 [1] Yuxin Sun, Zhengqing Fu, Peiyi Li, et al. Robotic digital twin: a lifecycle perspective from design to application and maintenance – a review[J]. Chain, 2026, 3(1): 37-52. DOI:10.23919/CHAIN.2026.000004.
MLA [1] Yuxin Sun, et al., "Robotic digital twin: a lifecycle perspective from design to application and maintenance – a review." Chain, vol. 3, no. 1, 2026, pp. 37-52, https://doi.org/10.23919/CHAIN.2026.000004.
APA [1] Yuxin Sun, Zhengqing Fu, Peiyi Li, Yadong Xu, Zhenhua Xiong, & Jinchen Ji. (2026). Robotic digital twin: a lifecycle perspective from design to application and maintenance – a review. Chain, 3(1), 37-52. https://doi.org/10.23919/CHAIN.2026.000004
IEEE [1] Yuxin Sun, Zhengqing Fu, Peiyi Li, Yadong Xu, Zhenhua Xiong, and Jinchen Ji, "Robotic digital twin: a lifecycle perspective from design to application and maintenance – a review," Chain, vol. 3, no. 1, pp. 37-52, 2026, doi: 10.23919/CHAIN.2026.000004. keywords: {AI;human-robot collaboration;real-time simulation;robotic digital twin;smart manufacturing}