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Distributed camouflage for swarm robotics and smart materials

Abstract

We present distributed algorithms for a swarm of static particles to camouflage in an environment by generating colored patterns similar to those perceived in the environment, mimicking the camouflage systems used by cephalopods. We assume each particle to be equipped with sensing, computation, and local communication abilities. For pattern recognition, each particle measures local color and brightness information, exchanges this information with its neighbors, determines local match with a library of patterns, and finally performs a consensus algorithm. For pattern formation, particles implement a distributed variant of Turing’s pattern generator. Together, these algorithms enable the swarm to obtain a high-level understanding of its environment and to quickly adapt its appearance to changing environments. All algorithms are evaluated on a swarm of 64 miniature robots (“Droplets”) that can sense and change color, and exchange information using directed infrared communication. With required computation being minimal and communication exclusively local, the system serves as a blueprint for further miniaturization and work in biomimetic camouflage.

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References

  1. Bian, P., Jin, Y., & Zhang, Nr. (2010). Fuzzy c-means clustering based digital camouflage pattern design and its evaluation. In Signal Processing (ICSP), 2010 IEEE 10th International Conference on, IEEE (pp. 1017–1020).

  2. Bradbury, J. W., & Vehrencamp, S. L., et al. (2011). Principles of animal communication. Sinauer Associates Sunderland.

  3. Butera, W. J., & Bove, Jr. V. M. (2002). Programming a paintable computer. PhD thesis, Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences.

  4. Chou, H. H., Nguyen, A., Chortos, A., To, J. W., Lu, C., Mei, J., Kurosawa, T., Bae, W. G., Tok, J. B. H., & Bao, Z. (2015). A chameleon-inspired stretchable electronic skin with interactive colour changing controlled by tactile sensing. Nature Communications 6.

  5. Farrow, N., Klingner, J., Reishus, D., & Correll, N. (2014). Miniature six-channel range and bearing system: algorithm, analysis and experimental validation. In 2014 IEEE International Conference on Robotics and Automation (ICRA), IEEE (pp. 6180–6185).

  6. Fekete, S. P., Fey, D., Komann, M., Kröller, A., Reichenbach, M., & Schmidt, C. (2009). Distributed vision with smart pixels. In Proceedings of the Twenty-fifth Annual Symposium on Computational Geometry, ACM (pp. 257–266).

  7. Fishman, A., Rossiter, J., & Homer, M. (2015). Hiding the squid: Patterns in artificial cephalopod skin. Journal of the Royal Society Interface, 12(108), 20150,281.

  8. Grossberg, S., Mingolla, E., & Ross, W. D. (1997). Visual brain and visual perception: How does the cortex do perceptual grouping? Trends in Neurosciences, 20(3), 106–111.

  9. Hanlon, R. (2007). Cephalopod dynamic camouflage. Current Biology, 17(11), R400–R404.

  10. Hanlon, R. T., & Messenger, J. B. (1988). Adaptive coloration in young cuttlefish (sepia officinalis l.): The morphology and development of body patterns and their relation to behaviour. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 320(1200), 437–487.

  11. Inami, M., Kawakami, N., & Tachi, S. (2003). Optical camouflage using retro-reflective projection technology. In Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality, IEEE Computer Society (p. 348).

  12. Jain, R., Kasturi, R., & Schunck, B. G. (1995). Machine vision (Vol. 5). New York: McGraw-Hill.

  13. Kelman, E. J., Osorio, D., & Baddeley, R. J. (2008). A review of cuttlefish camouflage and object recognition and evidence for depth perception. Journal of Experimental Biology, 211(11), 1757–1763.

  14. Klingner, J., Kanakia, A., Farrow, N., Dustin, R., & Correll, N. (2014). A stick-slip omnidirectional drive-train for low-cost swarm robotics: Mechanism, calibration, and control. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 846–851).

  15. Kondo, S., & Miura, T. (2010). Reaction-diffusion model as a framework for understanding biological pattern formation. Science, 329(5999), 1616–1620.

  16. Lamme, V. A. (1995). The neurophysiology of figure-ground segregation in primary visual cortex. Journal of Neuroscience, 15(2), 1605–1615.

  17. Lasbury, M. E. (2017). Cloaking devices: Vanishing into thin space. In The Realization of Star Trek Technologies, Springer (pp. 35–66).

  18. Lin, H. Y., Lie, W. N., & Wang, M. L. (2009). A framework of view-dependent planar scene active camouflage. International Journal of Imaging Systems and Technology, 19(3), 167–174.

  19. Meinhardt, H. (1982). Models of biological pattern formation (Vol. 6). London: Academic Press.

  20. Meinhardt, H. (2009). The algorithmic beauty of sea shells. Berlin: Springer.

  21. Meinhardt, H., & Gierer, A. (2000). Pattern formation by local self-activation and lateral inhibition. Bioessays, 22(8), 753–760.

  22. Messenger, J. B. (1977). Evidence that octopus is colour blind. Journal of Experimental Biology, 70(1), 49–55.

  23. Messenger, J. B. (2001). Cephalopod chromatophores: Neurobiology and natural history. Biological Reviews, 76(4), 473–528.

  24. Mirollo, R. E., & Strogatz, S. H. (1990). Synchronization of pulse-coupled biological oscillators. SIAM Journal on Applied Mathematics, 50(6), 1645–1662.

  25. Morin, S. A., Shepherd, R. F., Kwok, S. W., Stokes, A. A., Nemiroski, A., & Whitesides, G. M. (2012). Camouflage and display for soft machines. Science, 337(6096), 828–832.

  26. Otte, M. (2016). Collective cognition and sensing in robotic swarms via an emergent group-mind. In International Symposium on Experimental Robotics, Springer (pp. 829–840).

  27. Peek, J. E., Hepfinger, L., Balma, R., Christopher, G., Fleuriet, J., Honke, T., Huebner, G., Mauer, E., Dotoli, P., & Ronconi, P. et al. (2006). Guidelines for camouflage assessment using observers (instructions pour les evaluations de camouflage faisant appel a des observateurs)(cd-rom). Tech. rep., Nato Research and Technology Organization Neuilly-Sur-Seine (France).

  28. Pendry, J. B., Schurig, D., & Smith, D. R. (2006). Controlling electromagnetic fields. Science, 312(5781), 1780–1782.

  29. Ramirez, M. D., & Oakley, T. H. (2015). Eye-independent, light-activated chromatophore expansion (lace) and expression of phototransduction genes in the skin of octopus bimaculoides. Journal of Experimental Biology, 218(10), 1513–1520.

  30. Rossiter, J., Yap, B., & Conn, A. (2012). Biomimetic chromatophores for camouflage and soft active surfaces. Bioinspiration & Biomimetics, 7(3), 036,009.

  31. Smith, D. R. (2014). A cloaking coating for murky media. Science, 345(6195), 384–385.

  32. Stevens, M., & Merilaita, S. (2009). Animal camouflage: Current issues and new perspectives. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1516), 423–427.

  33. Stevens, M., & Merilaita, S. (2011). Animal camouflage: Mechanisms and function. Cambridge: Cambridge University Press.

  34. Stevens, M., Cuthill, I. C., Windsor, A. M., & Walker, H. J. (2006). Disruptive contrast in animal camouflage. Proceedings of the Royal Society of London B: Biological Sciences, 273(1600), 2433–2438.

  35. Stuart-Fox, D., & Moussalli, A. (2009). Camouflage, communication and thermoregulation: Lessons from colour changing organisms. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1516), 463–470.

  36. Toet, A. (2000). Technical evaluation report. In Search and TargetAcquisition: NATO RTO Meeting Proceedings (vol. 45).

  37. Troscianko, T., Benton, C. P., Lovell, P. G., Tolhurst, D. J., & Pizlo, Z. (2009). Camouflage and visual perception. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 364(1516), 449–461.

  38. Turing, A. M. (1952). The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 237(641), 37–72.

  39. Wang, Q., Gossweiler, G. R., Craig, S. L., & Zhao, X. (2014). Cephalopod-inspired design of electro-mechano-chemically responsive elastomers for on-demand fluorescent patterning. Nature Communications 5.

  40. Webb, B. (2001). Can robots make good models of biological behaviour? Behavioral and Brain Sciences, 24(06), 1033–1050.

  41. Werner-Allen, G., Tewari, G., Patel, A., Welsh, M., & Nagpal, R. (2005). Firefly-inspired sensor network synchronicity with realistic radio effects. In Proceedings of the Third International Conference on Embedded Networked Sensor Systems, ACM (pp. 142–153).

  42. Xiao, L., Boyd, S., & Lall, S. (2005). A scheme for robust distributed sensor fusion based on average consensus. In Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on, IEEE (pp. 63–70).

  43. Ying, X. (2007). Camouflage color selection based on dominant color extraction. Opto-Electronic Engineering, 1, 025.

  44. Young, D. A. (1984). A local activator-inhibitor model of vertebrate skin patterns. Mathematical Biosciences, 72(1), 51–58.

  45. Yu, C., Li, Y., Zhang, X., Huang, X., Malyarchuk, V., Wang, S., et al. (2014). Adaptive optoelectronic camouflage systems with designs inspired by cephalopod skins. Proceedings of the National Academy of Sciences, 111(36), 12,998–13,003.

  46. Zylinski, S., Osorio, D., & Shohet, A. (2009). Perception of edges and visual texture in the camouflage of the common cuttlefish, sepia officinalis. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 364(1516), 439–448.

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Acknowledgements

This research has been supported by NSF Grant #1150223 and by the Airforce Office of Scientific Research.

Author information

Correspondence to Yang Li.

Additional information

This is one of several papers published in Autonomous Robots comprising the “Special Issue on Distributed Robotics: From Fundamentals to Applications”.

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Li, Y., Klingner, J. & Correll, N. Distributed camouflage for swarm robotics and smart materials. Auton Robot 42, 1635–1650 (2018). https://doi.org/10.1007/s10514-018-9717-6

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Keywords

  • Smart materials
  • Swarm robotics
  • Autonomous robots
  • Artificial camouflage