Skip to main content
SpringerLink
Log in

Closed-loop interactions between a shoal of zebrafish and a group of robotic fish in a circular corridor

  • Published:
Swarm Intelligence Aims and scope Submit manuscript

Abstract

Collective behavior based on self-organization has been observed in populations of animals from insects to vertebrates. These findings have motivated engineers to investigate approaches to control autonomous multi-robot systems able to reproduce collective animal behaviors, and even to collectively interact with groups of animals. In this article, we show collective decision making by a group of autonomous robots and a group of zebrafish, leading to a shared decision about swimming direction. The robots can also modulate the collective decision-making process in biased and non-biased experimental setups. These results demonstrate the possibility of creating mixed societies of vertebrates and robots in order to study or control animal behavior.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Abaid, N., Bartolini, T., Macri, S., & Porfiri, M. (2012). Zebrafish responds differentially to a robotic fish of varying aspect ratio, tail beat frequency, noise, and color. Behavioural Brain Research, 233(2), 545–553.

    Article  Google Scholar 

  • Abaid, N., Marras, S., Fitzgibbons, C., & Porfiri, M. (2013). Modulation of risk-taking behaviour in golden shiners (Notemigonus crysoleucas) using robotic fish. Behavioural Processes, 100, 9–12.

    Article  Google Scholar 

  • Abaid, N., & Porfiri, M. (2010). Fish in a ring: Spatio-temporal pattern formation in one-dimensional animal groups. Journal of The Royal Society Interface, page rsif20100175.

  • Bartolini, T., Mwaffo, V., Showler, A., Macrì, S., Butail, S., & Porfiri, M. (2016). Zebrafish response to 3D printed shoals of conspecifics: The effect of body size. Bioinspiration & Biomimetics, 11(2), 026003.

    Article  Google Scholar 

  • Bonnet, F., Binder, S., de Oliveria, M. E., Halloy, J., & Mondada, F. (2014). A miniature mobile robot developed to be socially integrated with species of small fish. In IEEE international conference on robotics and biomimetics (ROBIO) 2014 (pp. 747–752).

  • Bonnet, F., Retornaz, P., Halloy, J., Gribovskiy, A., & Mondada, F. (2012). Development of a mobile robot to study the collective behavior of zebrafish. In 2012 4th IEEE RAS EMBS international conference on biomedical robotics and biomechatronics (BioRob) (pp. 437–442).

  • Bradski, G. (2000). The OpenCV Library. Dr. Dobb’s Journal: Software Tools for the Professional Programmer, 25(11), 120–123.

  • Braitenberg, V. (1986). Vehicles: Experiments in synthetic psychology. Cambridge: MIT Press.

    Google Scholar 

  • Butail, S., Bartolini, T., & Porfiri, M. (2013). Collective response of zebrafish shoals to a free-swimming robotic fish. PLoS One, 8(10), e76123.

    Article  Google Scholar 

  • Butail, S., Ladu, F., Spinello, D., & Porfiri, M. (2014a). Information flow in animal–robot interactions. Entropy, 16(3), 1315–1330.

    Article  Google Scholar 

  • Butail, S., Polverino, G., Phamduy, P., Del Sette, F., & Porfiri, M. (2014b). Fish–robot interactions in a free-swimming environment: Effects of speed and configuration of robots on live fish. In SPIE smart structures and materials \(+\) nondestructive evaluation and health monitoring, 2014 (Vol. 8).

  • Cazenille, L., Chemtob, Y., Bonnet, F., Gribovskiy, A., Mondada, F., Bredeche, N., & Halloy, J. (2017). Automated calibration of a biomimetic space-dependent model for zebrafish and robot collective behaviour in a structured environment. In Conference on biomimetic and biohybrid systems (pp. 107–118). Berlin: Springer.

  • Cianca, V., Bartolini, T., Porfiri, M., & Macrì, S. (2013). A robotics-based behavioral paradigm to measure anxiety-related responses in zebrafish. PLoS ONE, 8(7), e69661.

    Article  Google Scholar 

  • Correll, N., Schwager, M., & Rus, D. (2008). Social control of herd animals by integration of artificially controlled congeners. In From animals to animats 10: 10th International conference on simulation of adaptive behavior (pp. 437–446).

  • Donati, E., Worm, M., Mintchev, S., van der Wiel, M., Benelli, G., von der Emde, G., et al. (2016). Investigation of collective behaviour and electrocommunication in the weakly electric fish, mormyrus rume, through a biomimetic robotic dummy fish. Bioinspiration and Biomimetics, 11(6), 066009.

    Article  Google Scholar 

  • Faria, J. J., Dyer, J. R., Clément, R. O., Couzin, I. D., Holt, N., Ward, A. J., et al. (2010). A novel method for investigating the collective behaviour of fish: Introducing robofish. Behavioral Ecology and Sociobiology, 64(8), 1211–1218.

    Article  Google Scholar 

  • Fleisch, V. C., & Neuhauss, S. C. (2006). Visual behavior in zebrafish. Zebrafish, 3(2), 191–201.

    Article  Google Scholar 

  • Garnier, S. (2011). From ants to robots and back: How robotics can contribute to the study of collective animal behavior. In Y. Meng & Y. Jin (Eds.), Bio-inspired self-organizing robotic systems (pp. 105–120). Berlin, Heidelberg: Springer.

  • Griparic, K., Haus, T., Miklic, D., & Bogdan, S. (2015). Combined actuator sensor unit for interaction with honeybees. In Sensors applications symposium (SAS), 2015 (pp. 1–5).

  • Halloy, J., Sempo, G., Caprari, G., Rivault, C., Asadpour, M., Tache, F., et al. (2007). Social integration of robots into groups of cockroaches to control self-organized choices. Science, 318(5853), 1155–1158.

    Article  Google Scholar 

  • Jiang, L., Giuggioli, L., Perna, A., Escobedo, R., Lecheval, V., Sire, C., et al. (2017). Identifying influential neighbors in animal flocking. PLoS Computational Biology, 13(11), e1005822.

    Article  Google Scholar 

  • KaewTraKulPong, P., & Bowden, R. (2002). An improved adaptive background mixture model for real-time tracking with shadow detection. Video-Based Surveillance Systems, 1, 135–144.

    Article  Google Scholar 

  • Kawabata, K., Aonuma, H., Hosoda, K., & Xue, J. (2013). A system for automated interaction with the cricket utilizing a micro mobile robot. Journal of Robotics and Mechatronics, 25(2), 333–339.

    Article  Google Scholar 

  • Kopman, V., Laut, J., Polverino, G., & Porfiri, M. (2013). Closed-loop control of zebrafish response using a bioinspired robotic-fish in a preference test. Journal of the Royal Society Interface, 10(78), 20120540.

    Article  Google Scholar 

  • Krause, J., Hoare, D., Krause, S., Hemelrijk, C., & Rubenstein, D. (2000). Leadership in fish shoals. Fish and Fisheries, 1(1), 82–89.

    Article  Google Scholar 

  • Krause, J., Winfield, A. F., & Deneubourg, J.-L. (2011). Interactive robots in experimental biology. Trends in Ecology and Evolution, 26(7), 369–375.

    Article  Google Scholar 

  • Ladu, F., Bartolini, T., Panitz, S. G., Chiarotti, F., Butail, S., Macrì, S., et al. (2015a). Live predators, robots, and computer-animated images elicit differential avoidance responses in zebrafish. Zebrafish, 12(3), 205–214.

    Article  Google Scholar 

  • Ladu, F., Mwaffo, V., Li, J., Macrì, S., & Porfiri, M. (2015b). Acute caffeine administration affects zebrafish response to a robotic stimulus. Behavioural Brain Research, 289, 48–54.

    Article  Google Scholar 

  • Landgraf, T., Bierbach, D., Nguyen, H., Muggelberg, N., Romanczuk, P., & Krause, J. (2016). Robofish: Increased acceptance of interactive robotic fish with realistic eyes and natural motion patterns by live Trinidadian guppies. Bioinspiration & biomimetics, 11(1), 015001.

    Article  Google Scholar 

  • Landgraf, T., Nguyen, H., Forgo, S., Schneider, J., Schröer, J., Krüger, C., et al. (2013). Interactive robotic fish for the analysis of swarm behavior. In International conference in swarm intelligence (pp. 1–10). Berlin: Springer.

  • Landgraf, T., Oertel, M., Rhiel, D., & Rojas, R. (2010). A biomimetic honeybee robot for the analysis of the honeybee dance communication system. In IEEE/RSJ international conference on intelligent robots and systems (IROS), 2010, (pp. 3097–3102).

  • Laschi, C., Mazzolai, B., Patanè, F., Mattoli, V., Dario, P., Ishii, H., et al. (2006). Design and development of a legged rat robot for studying animal–robot interaction. In The first IEEE/RAS-EMBS international conference on biomedical robotics and biomechatronics (BioRob) 2006 (pp. 631–636).

  • Le Maho, Y., Whittington, J. D., Hanuise, N., Pereira, L., Boureau, M., Brucker, M., et al. (2014). Rovers minimize human disturbance in research on wild animals. Nature Methods, 11(12), 1242–1244.

    Article  Google Scholar 

  • Maaswinkel, H., & Li, L. (2003). Spatio-temporal frequency characteristics of the optomotor response in zebrafish. Vision Research, 43(1), 21–30.

    Article  Google Scholar 

  • Mondada, F., Martinoli, A., Correll, N., Gribovskiy, A., Halloy, J. I., Siegwart, R., & Deneubourg, J.-L. (2011). A general methodology for the control of mixed natural–artificial societies. Handbook of collective robotics (pp. 399–428).

  • Pérez-Escudero, A., Vicente-Page, J., Hinz, R. C., Arganda, S., & de Polavieja, G. G. (2014). idTracker: Tracking individuals in a group by automatic identification of unmarked animals. Nature Methods, 11(7), 743–748.

    Article  Google Scholar 

  • Phamduy, P., Polverino, G., Fuller, R., & Porfiri, M. (2014). Fish and robot dancing together: Bluefin killifish females respond differently to the courtship of a robot with varying color morphs. Bioinspiration & Biomimetics, 9(3), 036021.

    Article  Google Scholar 

  • Polverino, G., Abaid, N., Kopman, V., Macr, S., & Porfiri, M. (2012). Zebrafish response to robotic fish: Preference experiments on isolated individuals and small shoals. Bioinspiration & Biomimetics, 7(3), 036019.

    Article  Google Scholar 

  • Polverino, G., & Porfiri, M. (2013a). Mosquitofish (Gambusia affinis) responds differentially to a robotic fish of varying swimming depth and aspect ratio. Behavioural Brain Research, 250, 133–138.

    Article  Google Scholar 

  • Polverino, G., & Porfiri, M. (2013b). Zebrafish (Danio rerio) behavioural response to bioinspired robotic fish and mosquitofish (Gambusia affinis). Bioinspiration and Biomimetics, 8(4), 044001.

    Article  Google Scholar 

  • Rashid, M. T., Frasca, M., Ali, A. A., Ali, R. S., Fortuna, L., & Xibilia, M. G. (2012). Artemia swarm dynamics and path tracking. Nonlinear Dynamics, 68(4), 555–563.

    Article  Google Scholar 

  • Romano, D., Benelli, G., Donati, E., Remorini, D., Canale, A., & Stefanini, C. (2017). Multiple cues produced by a robotic fish modulate aggressive behaviour in siamese fighting fishes. Scientific Reports, 7, 4667.

    Article  Google Scholar 

  • Ruberto, T., Mwaffo, V., Singh, S., Neri, D., & Porfiri, M. (2016). Zebrafish response to a robotic replica in three dimensions. Royal Society Open Science, 3(10), 160505.

    Article  Google Scholar 

  • Ruberto, T., Polverino, G., & Porfiri, M. (2017). How different is a 3D-printed replica from a conspecific in the eyes of a zebrafish? Journal of the Experimental Analysis of Behavior, 107(2), 279–293.

    Article  Google Scholar 

  • Rundus, A. S., Owings, D. H., Joshi, S. S., Chinn, E., & Giannini, N. (2007). Ground squirrels use an infrared signal to deter rattlesnake predation. Proceedings of the National Academy of Sciences, 104(36), 14372–14376.

    Article  Google Scholar 

  • Séguret, A., Collignon, B., & Halloy, J. (2016). Strain differences in the collective behaviour of zebrafish (Danio rerio) in heterogeneous environment. Royal Society Open Science, 3(10), 160451.

    Article  Google Scholar 

  • Shi, J., & Tomasi, C. (1994). Good features to track. In IEEE computer society conference on computer vision and pattern recognition (CVPR), 1994 (pp. 593–600).

  • Shi, Q., Miyagishima, S., Konno, S., Fumino, S., Ishii, H., Takanishii, A., et al. (2010). Development of the hybrid wheel-legged mobile robot WR-3 designed to interact with rats. In 3rd IEEE RAS and EMBS international conference on biomedical robotics and biomechatronics (BioRob) (pp. 887–892).

  • Spence, R., Gerlach, G., Lawrence, C., & Smith, C. (2008). The behaviour and ecology of the zebrafish, Danio rerio. Biological Reviews of the Cambridge Philosophical Society, 83(1), 13–34.

    Article  Google Scholar 

  • Spinello, C., Macrì, S., & Porfiri, M. (2013). Acute ethanol administration affects zebrafish preference for a biologically inspired robot. Alcohol, 47(5), 391–398.

    Article  Google Scholar 

  • Swain, D. T., Couzin, I. D., & Leonard, N. E. (2012). Real-time feedback-controlled robotic fish for behavioral experiments with fish schools. Proceedings of the IEEE, 100(1), 150–163.

    Article  Google Scholar 

  • Taylor, R. C., Klein, B. A., Stein, J., & Ryan, M. J. (2008). Faux frogs: Multimodal signalling and the value of robotics in animal behaviour. Animal Behaviour, 76(3), 1089–1097.

    Article  Google Scholar 

  • Vaughan, R. T., Sumpter, N., Henderson, J., Frost, A., & Cameron, S. (2000). Experiments in automatic flock control. Robotics and Autonomous Systems, 31(1–2), 109–117.

    Article  Google Scholar 

  • Ward, A. J., Herbert-Read, J. E., Jordan, L. A., James, R., Krause, J., Ma, Q., et al. (2013). Initiators, leaders, and recruitment mechanisms in the collective movements of damselfish. The American Naturalist, 181(6), 748–760.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the EU-ICT Project ASSISIbf, No. 601074. The information provided is the sole responsibility of the authors and does not reflect the European Commission’s opinion. The European Commission is not responsible for any use that might be made of data appearing in this publication. We thank Leo Cazenille and Philippe Rétornaz for their assistance during the software and firmware implementation. We would also like to gratefully acknowledge Daniel Burnier and Norbert Crot for their technical support during the design and production of the robotic devices.

Author information

Authors and Affiliations

  1. Ecole Polytechnique Fédérale de Lausanne, EPFL STI IMT LSRO, ME B3 30 (Batiment ME), Station 9, 1015, Lausanne, Switzerland

    Frank Bonnet, Alexey Gribovskiy & Francesco Mondada

  2. Université Paris Diderot, Sorbonne Paris Cité, LIED, UMR 8236, 75013, Paris, France

    José Halloy

Authors
  1. Frank Bonnet
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexey Gribovskiy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. José Halloy
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Francesco Mondada
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Frank Bonnet.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (mp4 20651 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bonnet, F., Gribovskiy, A., Halloy, J. et al. Closed-loop interactions between a shoal of zebrafish and a group of robotic fish in a circular corridor. Swarm Intell 12, 227–244 (2018). https://doi.org/10.1007/s11721-017-0153-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11721-017-0153-6

Keywords

Search

Navigation