Skip to main content
SpringerLink
Log in

Materials That Make Robots Smart

  • Conference paper
  • First Online:
Robotics Research

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 10))

  • 2677 Accesses

Abstract

We posit that embodied artificial intelligence is not only a computational, but also a materials problem. While the importance of material and structural properties in the control loop are well understood, materials can take an active role during control by tight integration of sensors, actuators, computation and communication. We envision such materials to abstract functionality, therefore making the construction of intelligent robots more straightforward and robust. For example, robots could be made of bones that measure load, muscles that move, skin that provides the robot with information about the kind and location of tactile sensations ranging from pressure, to texture and damage, eyes that extract high-level information, and brain material that provides computation in a scalable manner. Such materials will not resemble any existing engineered materials, but rather the heterogeneous components out of which their natural counterparts are made. We describe the state-of-the-art in so-called “robotic materials,” their opportunities for revolutionizing applications ranging from manipulation to autonomous driving, and open challenges the robotics community needs to address in collaboration with allies, such as wireless sensor network researchers and polymer scientists.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Agbinya, J.I.: Wireless Power Transfer, vol. 45. River Publishers, Aalborg (2015)

    Google Scholar 

  2. Asbeck, A.T., Kim, S., Cutkosky, M.R., Provancher, W.R., Lanzetta, M.: Scaling hard vertical surfaces with compliant microspine arrays. Int. J. Robot. Res. 25(12), 1165–1179 (2006)

    Article  Google Scholar 

  3. Bartlett, N.W., Tolley, M.T., Overvelde, J.T., Weaver, J.C., Mosadegh, B., Bertoldi, K., Whitesides, G.M., Wood, R.J.: A 3d-printed, functionally graded soft robot powered by combustion. Science 349(6244), 161–165 (2015)

    Article  Google Scholar 

  4. Bauer, S., Bauer-Gogonea, S., Graz, I., Kaltenbrunner, M., Keplinger, C., Schwödiauer, R.: 25th anniversary article: a soft future: from robots and sensor skin to energy harvesters. Adv. Mater. 26(1), 149–162 (2014)

    Article  Google Scholar 

  5. Berlin, A.A., Gabriel, K.J.: Distributed MEMS: new challenges for computation. IEEE Comput. Sci. Eng. 4(1), 12–16 (1997)

    Article  Google Scholar 

  6. Brostow, W., Lobland, H.E.H.: Materials: Introduction and Applications. Wiley, New York (2016)

    Google Scholar 

  7. Cloney, R.A., Florey, E.: Ultrastructure of cephalopod chromatophore organs. Cell Tissue Res. 89(2), 250–280 (1968)

    Google Scholar 

  8. Correll, N., Önal, Ç.D., Liang, H., Schoenfeld, E., Rus, D.: Soft autonomous materials using active elasticity and embedded distributed computation. Experimental Robotics, pp. 227–240. Springer, Berlin (2014)

    Google Scholar 

  9. Cutkosky, M.R., Kim, S.: Design and fabrication of multi-material structures for bioinspired robots. Philos. Trans. R. Soc. Lond. A: Math. Phys. Eng. Sci. 367(1894), 1799–1813 (2009)

    Article  Google Scholar 

  10. Farrow, N., Sivagnanadasan, N., Correll, N.: Gesture based distributed user interaction system for a reconfigurable self-organizing smart wall. In: Proceedings of the 8th International Conference on Tangible, Embedded and Embodied Interaction, pp. 245–246. ACM (2014)

    Google Scholar 

  11. Farrow, N., Li, Y., Correll, N.: Morphological and embedded computation in a self-contained soft robotic hand (2016). arXiv:1605.00354

  12. Han, R., Correll, N., Pister, K., Dutta, P.: New directions: wireless robotic materials. In: 15th ACM Conference on Embedded Networked Sensor Systems (SenSys), Delft, The Netherlands (2017)

    Google Scholar 

  13. Hosseinmardi, H., Mysore, A., Farrow, N., Correll, N., Han, R.: Distributed spatiotemporal gesture recognition in sensor arrays. ACM Trans. Auton. Adapt. Syst. (TAAS) 10(3), 17 (2015)

    Google Scholar 

  14. Hughes, D., Correll, N.: Texture recognition and localization in amorphous robotic skin. Bioinspiration Biomim. 10(5), 055002 (2015)

    Google Scholar 

  15. Hughes, D., Farrow, N., Profita, H., Correll, N.: Detecting and identifying tactile gestures using deep autoencoders, geometric moments and gesture level features. In: Proceedings of the 2015 ACM on International Conference on Multimodal Interaction, pp. 415–422. ACM (2015)

    Google Scholar 

  16. Hughes, D., Heckman, C., Correll, N.: Terrain sensitive tires for autonomous driving. In: Workshop on Material Robotics at Robotics, Science and Systems (RSS), Cambridge, MA (2017)

    Google Scholar 

  17. Keplinger, C., Sun, J.-Y., Foo, C.C., Rothemund, P., Whitesides, G.M., Suo, Z.: Stretchable, transparent, ionic conductors. Science 341(6149), 984–987 (2013)

    Article  Google Scholar 

  18. Kim, S., Clark, J.E., Cutkosky, M.R.: iSprawl: design and tuning for high-speed autonomous open-loop running. Int. J. Robot. Res. 25(9), 903–912 (2006)

    Article  Google Scholar 

  19. Li, Y., Klingner, J., Correll, N.: Distributed camouflage for swarm robotics and smart materials. In: Distributed Autonomous Robotic Systems (DARS) (2016)

    Google Scholar 

  20. Marchese, A.D., Onal, C.D., Rus, D.: Autonomous soft robotic fish capable of escape maneuvers using fluidic elastomer actuators. Soft Robot. 1(1), 75–87 (2014)

    Article  Google Scholar 

  21. McEvoy, M., Correll, N.: Shape change through programmable stiffness. Experimental Robotics, pp. 893–907. Springer, Berlin (2016)

    Google Scholar 

  22. McEvoy, M.A., Correll, N.: Materials that couple sensing, actuation, computation and communication. Science 347(6228) (2015)

    Google Scholar 

  23. McEvoy, M.A., Correll, N.: Distributed inverse kinematics for shape-changing robotic materials. Procedia Technol. 26, 4–11 (2016)

    Article  Google Scholar 

  24. Moffo, D., Canalda, P., Spies, F.: Relative and absolute positioning in ultra dense MEMS system. In: 2016 IEEE International Conference on Computer and Information Technology (CIT), pp. 140–147. IEEE (2016)

    Google Scholar 

  25. O’Donnell, J., Kim, M., Yoon, H.-S.: A review on electromechanical devices fabricated by additive manufacturing. J. Manuf. Sci. Eng. 139(1), 010801 (2017)

    Google Scholar 

  26. Pannuto, P., Andersen, M.P., Bauer, T., Campbell, B., Levy, A., Culler, D., Levis, P., Dutta, P.: A networked embedded system platform for the post-mote era. In: Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems, pp. 354–355. ACM (2014)

    Google Scholar 

  27. Patel, R., Cox, R., Romero, B., Correll, N.: Improving grasp performance using in-hand proximity and contact sensing (2017). arXiv:1701.06071

  28. Pfeifer, R., Iida, F., Gómez, G.: Morphological computation for adaptive behavior and cognition. International Congress Series, vol. 1291, pp. 22–29. Elsevier, Amsterdam (2006)

    Google Scholar 

  29. Polygerinos, P., Correll, N., Morin, S.A., Mosadegh, B., Onal, C.D., Petersen, K., Cianchetti, M., Tolley, M.T., Shepherd, R.F.: Soft robotics: review of fluid-driven intrinsically soft devices; manufacturing, sensing, control, and applications in human-robot interaction. Adv. Eng. Materials

    Google Scholar 

  30. Profita, H., Farrow, N., Correll, N.: Flutter: an exploration of an assistive garment using distributed sensing, computation and actuation. In: Proceedings of the Ninth International Conference on Tangible, Embedded, and Embodied Interaction, pp. 359–362. ACM (2015)

    Google Scholar 

  31. Tolley, M.T., Shepherd, R.F., Karpelson, M., Bartlett, N.W., Galloway, K.C., Wehner, M., Nunes, R., Whitesides, G.M., Wood, R.J.: An untethered jumping soft robot. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), pp. 561–566. IEEE (2014)

    Google Scholar 

  32. Xie, X.-L., Mai, Y.-W., Zhou, X.-P.: Dispersion and alignment of carbon nanotubes in polymer matrix: a review. Mater. Sci. Eng.: R: Rep. 49(4), 89–112 (2005)

    Article  Google Scholar 

Download references

Acknowledgements

This work was sponsored by ARO under grant number W911NF-16-1-0476, program manager S. Stanton, by AFOSR, program manager B. “Les” Lee, and DARPA award no. N65236–16–1–1000. We are grateful for this support.

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Colorado, Boulder, CO, USA

    Nikolaus Correll & Christoffer Heckman

  2. Material Science Engineering, University of Colorado, Boulder, CO, USA

    Nikolaus Correll

Authors
  1. Nikolaus Correll
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christoffer Heckman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nikolaus Correll .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Nancy M. Amato

  2. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

    Greg Hager

  3. Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA

    Shawna Thomas

  4. Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

    Miguel Torres-Torriti

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Correll, N., Heckman, C. (2020). Materials That Make Robots Smart. In: Amato, N., Hager, G., Thomas, S., Torres-Torriti, M. (eds) Robotics Research. Springer Proceedings in Advanced Robotics, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-030-28619-4_6

Download citation

Publish with us

Policies and ethics

Search

Navigation