Controlling the dynamic behavior of decentralized cluster through centralized approaches

doi:10.1088/1674-1056/ad3dd0

中国物理B ›› 2024, Vol. 33 ›› Issue (6): 60702-060702.doi: 10.1088/1674-1056/ad3dd0

Controlling the dynamic behavior of decentralized cluster through centralized approaches

Daming Yuan(袁大明)^1,†, Peilong Wang(王培龙)^1,†, Peng Wang(王鹏)², Xingyu Ma(马星宇)¹, Chuyun Wang(汪楚云)², Jing Wang(王璟)³, Huaicheng Chen(陈怀城)³, Gao Wang(王高)^3,4,‡, and Fangfu Ye(叶方富)^1,3,§

1 School of Ophthalmology and Optometry, Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou 325035, China;
2 Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou 325035, China;
3 Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou 325011, China;
4 School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China

收稿日期:2024-02-06 修回日期:2024-03-13 出版日期:2024-06-18 发布日期:2024-06-18
通讯作者: Gao Wang, Fangfu Ye E-mail:wanggao@ucas.ac.cn;ye@iphy.ac.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 12174041), China Postdoctoral Science Foundation (CPSF) (Grant No. 2022M723118), and the seed grants from the Wenzhou Institute, University of Chinese Academy of Sciences (Grant No. WIUCASQD2021002).

Controlling the dynamic behavior of decentralized cluster through centralized approaches

1 School of Ophthalmology and Optometry, Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou 325035, China;
2 Postgraduate Training Base Alliance, Wenzhou Medical University, Wenzhou 325035, China;
3 Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou 325011, China;
4 School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2024-02-06 Revised:2024-03-13 Online:2024-06-18 Published:2024-06-18
Contact: Gao Wang, Fangfu Ye E-mail:wanggao@ucas.ac.cn;ye@iphy.ac.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 12174041), China Postdoctoral Science Foundation (CPSF) (Grant No. 2022M723118), and the seed grants from the Wenzhou Institute, University of Chinese Academy of Sciences (Grant No. WIUCASQD2021002).

摘要/Abstract

摘要： How to control the dynamic behavior of large-scale artificial active matter is a critical concern in experimental research on soft matter, particularly regarding the emergence of collective behaviors and the formation of group patterns. Centralized systems excel in precise control over individual behavior within a group, ensuring high accuracy and controllability in task execution. Nevertheless, their sensitivity to group size may limit their adaptability to diverse tasks. In contrast, decentralized systems empower individuals with autonomous decision-making, enhancing adaptability and system robustness. Yet, this flexibility comes at the cost of reduced accuracy and efficiency in task execution. In this work, we present a unique method for regulating the centralized dynamic behavior of self-organizing clusters based on environmental interactions. Within this environment-coupled robot system, each robot possesses similar dynamic characteristics, and their internal programs are entirely identical. However, their behaviors can be guided by the centralized control of the environment, facilitating the accomplishment of diverse cluster tasks. This approach aims to balance the accuracy and flexibility of centralized control with the robustness and task adaptability of decentralized control. The proactive regulation of dynamic behavioral characteristics in active matter groups, demonstrated in this work through environmental interactions, holds the potential to introduce a novel technological approach and provide experimental references for studying the dynamic behavior control of large-scale artificial active matter systems.

关键词: self-organizing system, centralized control, dynamics regulation

Abstract: How to control the dynamic behavior of large-scale artificial active matter is a critical concern in experimental research on soft matter, particularly regarding the emergence of collective behaviors and the formation of group patterns. Centralized systems excel in precise control over individual behavior within a group, ensuring high accuracy and controllability in task execution. Nevertheless, their sensitivity to group size may limit their adaptability to diverse tasks. In contrast, decentralized systems empower individuals with autonomous decision-making, enhancing adaptability and system robustness. Yet, this flexibility comes at the cost of reduced accuracy and efficiency in task execution. In this work, we present a unique method for regulating the centralized dynamic behavior of self-organizing clusters based on environmental interactions. Within this environment-coupled robot system, each robot possesses similar dynamic characteristics, and their internal programs are entirely identical. However, their behaviors can be guided by the centralized control of the environment, facilitating the accomplishment of diverse cluster tasks. This approach aims to balance the accuracy and flexibility of centralized control with the robustness and task adaptability of decentralized control. The proactive regulation of dynamic behavioral characteristics in active matter groups, demonstrated in this work through environmental interactions, holds the potential to introduce a novel technological approach and provide experimental references for studying the dynamic behavior control of large-scale artificial active matter systems.

Key words: self-organizing system, centralized control, dynamics regulation

中图分类号: (Control systems)

07.05.Dz

45.70.Qj (Pattern formation) 45.40.Ln (Robotics)

Daming Yuan(袁大明), Peilong Wang(王培龙), Peng Wang(王鹏), Xingyu Ma(马星宇), Chuyun Wang(汪楚云), Jing Wang(王璟), Huaicheng Chen(陈怀城), Gao Wang(王高), and Fangfu Ye(叶方富). Controlling the dynamic behavior of decentralized cluster through centralized approaches[J]. 中国物理B, 2024, 33(6): 60702-060702.

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Controlling the dynamic behavior of decentralized cluster through centralized approaches

Controlling the dynamic behavior of decentralized cluster through centralized approaches

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