Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

Phototactic supersmarticles

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

Smarticles or smart active particles are small robots equipped with only basic movement and sensing abilities that are incapable of rotating or displacing individually. We study the ensemble behavior of smarticles, i.e., the behavior a collective of these very simple computational elements can achieve, and how such behavior can be implemented using minimal programming. We show that an ensemble of smarticles constrained to remain close to one another (which we call a supersmarticle), achieves directed locomotion toward or away from a light source, a phenomenon known as phototaxing. We present experimental and theoretical models of phototactic supersmarticles that collectively move with a directed displacement in response to light. The motion of the supersmarticle is stochastic, performing approximate free diffusion, and is a result of chaotic interactions among smarticles. The system can be directed by introducing asymmetries among the individual smarticle’s behavior, in our case, by varying activity levels in response to light, resulting in supersmarticle-biased motion.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. As opposed to passive programmable matter systems such as DNA computing and tile self-assembly.

  2. The assumption of connectedness can be relaxed, but it simplifies the proofs while maintaining the phototaxing behavior we desire. We can think of connectivity and compression as playing a role analogous to that of the ring in the physical model.

References

  1. Ramaswamy S (2010) The mechanics and statistics of active matter. Annu Rev Condens Matter Phys 1(1):323–345. https://doi.org/10.1146/annurev-conmatphys-070909-104101

    Article  Google Scholar 

  2. Derakhshandeh Z, Gmyr R, Richa AW, Scheideler C, Strothmann T (2017) Universal coating for programmable matter. Theor Comput Sci 671:56

    Article  MathSciNet  Google Scholar 

  3. Cannon S, Daymude JJ, Randall D, Richa AW (2016) A Markov chain algorithm for compression in self-organizing particle systems. In: Proc. of the 2016 ACM Symposium on Principles of Distributed Computing (PODC ’16), pp 279–288

  4. Mlot NJ, Tovey CA, Hu DL (2011) Fire ants self-assemble into waterproof rafts to survive floods. Proc Natl Acad Sci 108(19):7669

    Article  Google Scholar 

  5. Cheung KC, Demaine ED, Bachrach JR, Griffith S (2011) Programmable assembly with universally foldable strings (Moteins). IEEE Trans Robot 27(4):718

    Article  Google Scholar 

  6. Woods D (2013) Intrinsic universality and the computational power of self-assembly. In: Proceedings of machines, computations and universality 2013 (MCU ’13), pp 16–22

    Article  MathSciNet  Google Scholar 

  7. Angluin D, Aspnes J, Diamadi Z, Fischer MJ, Peralta R (2006) Computation in networks of passively mobile finite-state sensors. Distrib Comput 18(4):235

    Article  Google Scholar 

  8. Cieliebak M, Flocchini P, Prencipe G, Santoro N (2012) Distributed computing by mobile robots: gathering. SIAM J Comput 41(4):829

    Article  MathSciNet  Google Scholar 

  9. Rubenstein M, Cornejo A, Nagpal R (2014) Programmable self-assembly in a thousand-robot swarm. Science 345(6198):795

    Article  Google Scholar 

  10. Chazelle B (2009) Natural algorithms. In: Proceedings of the 2009 ACM-SIAM symposium on discrete algorithms (SODA09), pp 422–431

    Chapter  Google Scholar 

  11. Yim M, Shen WM, Salemi B, Rus D, Moll M, Lipson H, Klavins E, Chirikjian GS (2007) Modular self-reconfigurable robot systems. IEEE Robot Autom Mag 14(1):43

    Article  Google Scholar 

  12. Woods D, Chen HL, Goodfriend S, Dabby N, Winfree E, Yin P (2013) Active self-assembly of algorithmic shapes and patterns in polylogarithmic time. In: Proceedings of the 4th Innovations in Theoretical Computer Science Conference (ITCS ’13), pp 353–354

  13. Daymude JJ, Richa AW, Scheideler C (2017) The Amoebot model. The Mmoebot model. https://sops.engineering.asu.edu/sops/amoebot

  14. Junot G, Briand G, Ledesma-Alonso R, Dauchot O (2017) Active versus passive hard disks against a membrane: mechanical pressure and instability. Phys Rev Lett 119:028002

    Article  Google Scholar 

  15. Solon AP, Stenhammar J, Wittkowski R, Kardar M (2015) Pressure and phase equilibria in interacting active brownian spheres. Phys Rev Lett 114(19):198301

    Article  Google Scholar 

  16. Andrés Arroyo M, Cannon S, Daymude JJ, Randall D, Richa AW (2017) A stochastic approach to shortcut bridging in programmable matter. In: DNA computing and molecular programming, pp 122–138

    MATH  Google Scholar 

  17. Reid CR, Lutz MJ, Powell S, Kao AB, Couzin ID, Garnier S (2015) Army ants dynamically adjust living bridges in response to a cost-benefit trade-off. Proc Natl Acad Sci 112(49):15113

    Article  Google Scholar 

  18. Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21:1087

    Article  Google Scholar 

  19. Hastings WK (1970) Monte Carlo sampling methods using Markov Chains and their applications. Biometrika 57(1):97

    Article  MathSciNet  Google Scholar 

  20. Lynch N (1996) Distributed algorithms. Morgan Kauffman, Burlington

    MATH  Google Scholar 

  21. Tarantino N, Tinevez JY, Crowell E, Boisson B, Henriques R, Mhlanga M, Agou F, Israël A, Laplantine E (2014) TNF and IL-1 exhibit distinct ubiquitin requirements for inducing NEMO-IKK supramolecular structures. J Cell Biol 204(2):231

    Article  Google Scholar 

  22. Berg H (1983) Random walks in biology. Princeton University Press, Princeton

    Google Scholar 

Download references

Acknowledgements

S. Cannon: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. NSF DGE-1650044. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. J. J. Daymude and A. W. Richa: Supported in part by NSF CCF-1422603, CCF-1637393, and CCF-1733680. D. I. Goldman: Funding provided by NSF PoLS #0957659 and #PHY-1205878, and ARO #W911NF-13-1-0347. D. Randall: Supported in part by NSF CCF-1526900, CCF-1637031, and CCF-1733812.

Author information

Authors and Affiliations

  1. School of Physics, Georgia Institute of Technology, Atlanta, GA, USA

    William Savoie, Ross Warkentin, Shengkai Li & Daniel I. Goldman

  2. College of Computing, Georgia Institute of Technology, Atlanta, GA, USA

    Sarah Cannon & Dana Randall

  3. Computer Science, CIDSE, Arizona State University, Tempe, AZ, USA

    Joshua J. Daymude & Andréa W. Richa

Authors
  1. William Savoie
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sarah Cannon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Joshua J. Daymude
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ross Warkentin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shengkai Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Andréa W. Richa
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Dana Randall
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Daniel I. Goldman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daniel I. Goldman.

Additional information

This work was presented in part at the 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics, Kyoto, October 29–November 1, 2017.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Savoie, W., Cannon, S., Daymude, J.J. et al. Phototactic supersmarticles. Artif Life Robotics 23, 459–468 (2018). https://doi.org/10.1007/s10015-018-0473-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-018-0473-7

Keywords