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 College of Physics, Chongqing University, Chongqing 401331, China
Abstract The use of robotic swarms to study the properties of active matter is a common experimental approach. In such studies, robots are often required to possess capabilities in computation, storage, perception, and two-dimensional (2D) movement to execute predefined rules. Under these rules, the swarm can accomplish complex tasks, exhibit rich collective states, or demonstrate intriguing phase transition phenomena. However, this study demonstrates how a swarm of spin robots, which only respond to simple ambient light intensity, can be constructed into a collective system capable of performing practical swarm tasks such as phototactic motion, controllable folding, and object transport through weak coupling interactions between individuals. Furthermore, it is proven that this swarm exhibits strong system fault tolerance. This research aims to demonstrate that, beyond the common design of sophisticated individuals and excellent inter-individual interaction rules, appropriate structural and coupling designs can enable individuals without computational capabilities to generate complex collective behaviors and accomplish diverse swarm tasks through cooperation. This provides a research direction for experimental studies of active matter using robotic systems.
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. T2350007, 12404239, and 12174041) and the Seed Grants from the Wenzhou Institute, University of the Chinese Academy of Sciences (Grant No. WIUCASQD2021002).
Corresponding Authors:
Gao Wang, Liyu Liu
E-mail: wanggao@ucas.ac.cn;liu@iphy.ac.cn
Cite this article:
Xingyu Ma(马星宇), Chuyun Wang(汪楚云), Jing Wang(王璟), Huaicheng Chen(陈怀城), Gao Wang(王高), and Liyu Liu(刘雳宇) Simple robot swarm with magnetic coupling connections can collaboratively accomplish collective tasks 2025 Chin. Phys. B 34 068701
[1] Kaspar C, Ravoo B J, Van Der Wiel W G, Wegner S V and Pernice W H P 2021 Nature 594 345 [2] Dorigo M, Theraulaz G and Trianni V 2021 Proc. IEEE 109 1152 [3] Wang G, Phan T V, Li S, Wombacher M, Qu J, Peng Y, Chen G, Goldman D I, Levin S A, Austin R H and Liu L 2021 Phys. Rev. Lett. 126 108002 [4] Slavkov I, Carrillo-Zapata D, Carranza N, Diego X, Jansson F, Kaandorp J, Hauert S and Sharpe J 2018 Sci. Robot. 3 eaau9178 [5] Li S, Dutta B, Cannon S, Daymude J J, Avinery R, Aydin E, Richa A W, Goldman D I and Randall D 2021 Sci. Adv. 7 eabe8494 [6] Ceron S, Gardi G, Petersen K and Sitti M 2023 Proc. Natl. Acad. Sci. USA 120 e2221913120 [7] Wang G, Phan T V, Li S, Wang J, Peng Y, Chen G, Qu J, Goldman D I, Levin S A, Pienta K, Amend S, Austin R H and Liu L 2022 Proc. Natl. Acad. Sci. USA 119 e2120019119 [8] Jin Y, Wang G, Yuan D, Wang P, Wang J, Chen H, Liu L and Zan X 2023 Chin. Phys. B 32 088703 [9] Xie H, Sun M, Fan X, Lin Z, ChenW,Wang L, Dong L and He Q 2019 Sci. Robot. 4 eaav8006 [10] Bredeche N, Haasdijk E and Prieto A 2018 Front. Robot. AI 5 12 [11] Doncieux S, Bredeche N, Mouret J B and Eiben A E (Gusz) 2015 Front. Robot. AI 2 [12] Devlin M R, Kim S, Campàs O and Hawkes E W 2025 Science 387 880 [13] Saintyves B, Spenko M and Jaeger H M 2024 Sci. Robot. 9 eadh4130 [14] Wang J,Wang G, Chen H, Liu Y,Wang P, Yuan D, Ma X, Xu X, Cheng Z, Ji B, Yang M, Shuai J, Ye F, Wang J, Jiao Y and Liu L 2024 Nat. Commun. 15 8853 [15] Fruchart M, Hanai R, Littlewood P B and Vitelli V 2021 Nature 592 363 [16] Bonnet F, Mills R, Szopek M, Schönwetter-Fuchs S, Halloy J, Bogdan S, Correia L, Mondada F and Schmickl T 2019 Sci. Robot. 4 eaau7897 [17] Lavergne F A, Wendehenne H, Bäuerle T and Bechinger C 2019 Science 364 70 [18] Chen J, Lei X, Xiang Y, Duan M, Peng X and Zhang H P 2024 Phys. Rev. Lett. 132 118301 [19] Li S, Batra R, Brown D, Chang H D, Ranganathan N, Hoberman C, Rus D and Lipson H 2019 Nature 567 361 [20] Rubenstein M, Cornejo A and Nagpal R 2014 Science 345 795 [21] Aguilar W, SantamarA-a-Bonfil G, Froese T and Gershenson C 2014 Front. Robot. AI 1 [22] Duan H, Huo M and Fan Y 2023 Natl. Sci. Rev. 10 nwad040 [23] Chen C J and Bechinger C 2022 New J. Phys. 24 033001 [24] Mathews N, Christensen A L, O’Grady R, Mondada F and Dorigo M 2017 Nat. Commun. 8 439 [25] Berlinger F, Gauci M and Nagpal R 2021 Sci. Robot. 6 eabd8668 [26] SavoieW, Berrueta T A, Jackson Z, Pervan A,Warkentin R, Li S, Murphey T D,Wiesenfeld K and Goldman D I 2019 Sci. Robot. 4 eaax4316 [27] Aguilar J, Zhang T, Qian F, Kingsbury M, McInroe B, Mazouchova N, Li C, Maladen R, Gong C, Travers M, Hatton R L, Choset H, Umbanhowar P B and Goldman D I 2016 Rep. Prog. Phys. 79 110001 [28] Yuan D, Wang P, Wang P, Ma X, Wang C, Wang J, Chen H, Wang G and Ye F 2024 Chin. Phys. B 33 060702 [29] Woodhouse F G and Dunkel J 2017 Nat. Commun. 8 15169 [30] Chen J, Hu J and Kapral R 2024 Adv. Sci. 11 2305695 [31] Yang Q, Zhu H, Liu P, Liu R, Shi Q, Chen K, Zheng N, Ye F and Yang M 2021 Phys. Rev. Lett. 126 198001 [32] Soto F, Karshalev E, Zhang F, Esteban Fernandez De Avila B, Nourhani A and Wang J 2022 Chem. Rev. 122 5365 [33] Deblais A, Barois T, Guerin T, Delville P H, Vaudaine R, Lintuvuori J S, Boudet J F, Baret J C and Kellay H 2018 Phys. Rev. Lett. 120 188002 [34] Scholz C, Engel M and Pöschel T 2018 Nat. Commun. 9 931 [35] Gardi G, Ceron S,WangW, Petersen K and Sitti M 2022 Nat. Commun. 13 2239 [36] Porvatov V A, Rozenblit A D, Dmitriev A A, Burmistrov O I, Petrova D A, Gritsenko G Y, Puhtina E M, Kretov E I, Filonov D S, Souslov A and Olekhno N A 2021 J. Phys. Conf. Ser. 2086 012202 [37] Han Y, Alsayed A M, Nobili M, Zhang J, Lubensky T C and Yodh A G 2006 Science 314 626 [38] Rehfeldt F and Weiss M 2023 Soft Matter 19 5206 [39] Huang H W, Uslu F E, Katsamba P, Lauga E, Sakar M S and Nelson B J 2019 Sci. Adv. 5 eaau1532 [40] Yu W, Lin H, Wang Y, He X, Chen N, Sun K, Lo D, Cheng B, Yeung C, Tan J, Di Carlo D and Emaminejad S 2020 Sci. Robot. 5 eaba4411
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