Flexible control technology of industrial robot clusters: a survey

Manufacturing plants impose stringent requirements on the quality, efficiency and flexibility of batch production processes. Industrial robots, characterized by high flexibility, precision and reliability, have emerged as pivotal processing equipment in modern factories – particularly in the scenario of clustered flexible processing involving dozens or even hundreds of industrial robots. Through parallel collaboration among multi-robot systems and dynamic task allocation, not only can synchronous advancement of multiple manufacturing processes be achieved, but also equipment utilization efficiency and consistency of processing accuracy can be significantly improved, while enabling rapid switching of product processing procedures. Nevertheless, the current cluster control of industrial robots still suffers from several technical deficiencies. Specifically, the accuracy and real-time performance of collaborative control remain insufficient; the reliability and compatibility of communication links are compromised under conditions of high load, protocol heterogeneity and complex industrial environments; and the single-fault-tolerance mechanism may exert adverse impacts on production quality and efficiency. Against this backdrop, this paper reviews the research progress of industrial robot cluster control technologies in recent years, focusing on three core aspects: the robot cluster control framework, multi-robot collaborative control technologies, and anti-interference & fault-tolerance mechanisms. It systematically summarizes the characteristics, application scopes and existing limitations of these technologies, thereby providing valuable insights for the design and technical optimization of future industrial robot cluster control systems.

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Publication Details

Journal
Cogent Engineering
Published
2026-09-15
DOI
https://doi.org/10.1080/23311916.2026.2731010
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.00

Funders

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article

Flexible control technology of industrial robot clusters: a survey

Jiyun Zhang, Bing Wei, Ziheng Wang, Hongjian Zhao et al.
Cogent Engineering
Scheduling and Optimization Algorithms
article

Flexible control technology of industrial robot clusters: a survey

Jiyun Zhang, Bing Wei, Ziheng Wang, Hongjian Zhao, Yuxuan Yang, Haitao Wang
article en

Abstract

Manufacturing plants impose stringent requirements on the quality, efficiency and flexibility of batch production processes. Industrial robots, characterized by high flexibility, precision and reliability, have emerged as pivotal processing equipment in modern factories – particularly in the scenario of clustered flexible processing involving dozens or even hundreds of industrial robots. Through parallel collaboration among multi-robot systems and dynamic task allocation, not only can synchronous advancement of multiple manufacturing processes be achieved, but also equipment utilization efficiency and consistency of processing accuracy can be significantly improved, while enabling rapid switching of product processing procedures. Nevertheless, the current cluster control of industrial robots still suffers from several technical deficiencies. Specifically, the accuracy and real-time performance of collaborative control remain insufficient; the reliability and compatibility of communication links are compromised under conditions of high load, protocol heterogeneity and complex industrial environments; and the single-fault-tolerance mechanism may exert adverse impacts on production quality and efficiency. Against this backdrop, this paper reviews the research progress of industrial robot cluster control technologies in recent years, focusing on three core aspects: the robot cluster control framework, multi-robot collaborative control technologies, and anti-interference & fault-tolerance mechanisms. It systematically summarizes the characteristics, application scopes and existing limitations of these technologies, thereby providing valuable insights for the design and technical optimization of future industrial robot cluster control systems.

Cogent EngineeringVol. 13(1)
Beijing Research Institute of Automation for Machinery Industry (China) (CN)
National Science and Technology Major Project
Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Scheduling and Optimization Algorithms
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