Skip to main content

Research Outlook

  • Chapter
  • First Online:
Human-Robot Body Experience

Part of the book series: Springer Series on Touch and Haptic Systems ((SSTHS))

  • 456 Accesses

Abstract

Haptic interaction plays a crucial role in achieving the embodiment of robotic devices. This chapter suggests future research directions with respect to bi-directional human-machine interfaces and considering the whole variety of the sense of touch. Aiming at robotic devices that “feel good”, robots equipped with bi-directional human-machine interfaces can support neuroscientific studies to understand human cognition and identify technological challenges. To this end, a research roadmap suggests how to use technologies like haptic feedback with high spatial density and expansion, semi-autonomy, as well as intent detection. While multi-faceted tactile feedback is scarcely considered, it comprises highly relevant facets such as affective touch, social touch, or self-touch. Those kinds of feedback include non-instrumental aspects, might make a decisive contribution to device embodiment, and would benefit from technological developments of bi-directional interfaces. Discussing the related potentials, the content of this monograph is concluded and directions for cognitive modeling and human-in-the-loop experiments are discussed.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
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. Beckerle, P., Castellini, C., Lenggenhager, B.: Robotic interfaces for cognitive psychology and embodiment research: a research roadmap. Wiley Interdiscip. Rev.: Cogn. Sci. 10(2), e1486 (2019)

    Google Scholar 

  2. Apps, M.A., Tsakiris, M.: The free-energy self: a predictive coding account of self-recognition. Neurosci. Biobehav. Rev. 41, 85–97 (2014)

    Article  Google Scholar 

  3. Blanke, O.: Multisensory brain mechanisms of bodily self-consciousness. Nat. Rev. Neurosci. 13, 556–571 (2012)

    Article  Google Scholar 

  4. Blanke, O., Metzinger, T.: Full-body illusions and minimal phenomenal selfhood. Trends Cogn. Sci. 13(1), 7–13 (2009)

    Article  Google Scholar 

  5. Toet, A., Kuling, I.A., Krom, B.N., van Erp, J.B.F.: Toward enhanced teleoperation through embodiment. Front. Robot. AI 7, 14 (2020)

    Article  Google Scholar 

  6. Aymerich-Franch, L., Petit, D., Ganesh, G., Kheddar, A.: The second me: seeing the real body during humanoid robot embodiment produces an illusion of bi-location. Conscious. Cogn. 46, 99–109 (2016)

    Article  Google Scholar 

  7. Kappers, A.M.L., Bergmann Tiest, W.M.: Bayesian approaches to sensory integration for motor control. Wiley Interdiscip. Rev.: Cogn. Sci. 4(4), 357–374 (2013)

    Google Scholar 

  8. Rognini, G., Blanke, O.: Cognetics: robotic interfaces for the conscious mind. Trends Cogn. Sci. 20(3), 162–164 (2016)

    Article  Google Scholar 

  9. Le, T.H.L., Maiolino, P., Mastrogiovanni, F., Cannata, C.: Skinning a robot: design methodologies for large-scale robot skin. IEEE Robot. Autom. Mag. 23(4) (2016)

    Google Scholar 

  10. Büscher, G.H., Kõiva, R., Schürmann, C., Haschke, R., Ritter, H.J.: Flexible and stretchable fabric-based tactile sensor. Robot. Auton. Syst. 63, 244–252 (2015)

    Article  Google Scholar 

  11. Strbac, M., Belic, M., Isakovic, M., Kojic, V., Bijelic, G., Popovic, I., Radotic, M., Dosen, S., Markovic, M., Farina, D., Keller, T.: Integrated and flexible multichannel interface for electrotactile stimulation. J. Neural Eng. 13(4), 046,014 (2016)

    Google Scholar 

  12. Franceschi, M., Seminara, L., Došen, S., Štrbac, M., Valle, M., Farina, D.: A system for electrotactile feedback using electronic skin and flexible matrix electrodes: experimental evaluation. IEEE Trans. Haptics 10(2), 162–172 (2017)

    Article  Google Scholar 

  13. Beckerle, P., Salvietti, G., Unal, R., Prattichizzo, D., Rossi, S., Castellini, C., Hirche, S., Endo, S., Ben Amor, H., Ciocarlie, M., Mastrogiovanni, F., Argall, B.D., Bianchi, M.: A human-robot interaction perspective on assistive and rehabilitation robotics. Front. Neurorobot. 11(24) (2017)

    Google Scholar 

  14. Beckerle, P.: Commentary: proceedings of the first workshop on peripheral machine interfaces: going beyond traditional surface electromyography. Front. Neurorobot. 11:32 (2017)

    Google Scholar 

  15. Boessenkool, H., Abbink, D.A., Heemskerk, C.J.M., van der Helm, F.C.T., Wildenbeest, J.G.W.: A task-specific analysis of the benefit of haptic shared control during telemanipulation. IEEE Trans. Haptics 6(1), 2–12 (2013)

    Article  Google Scholar 

  16. Antuvan, C.W., Ison, M., Artemiadis, P.: Embedded human control of robots using myoelectric interfaces. IEEE Trans. Neural Syst. Rehabil. Eng. 22(4), 820–27 (2014). https://doi.org/10.1109/TNSRE.2014.2302212

    Article  Google Scholar 

  17. Hahne, J.M., Dähne, S., Hwang, H.J., Müller, K.R., Parra, L.C.: Concurrent adaptation of human and machine improves simultaneous and proportional myoelectric control. IEEE Trans. Neural Syst. Rehabil. Eng. 23(4), 618–627 (2015). https://doi.org/10.1109/TNSRE.2015.2401134

    Article  Google Scholar 

  18. Nowak, M., Bongers, R.M., van der Sluis, C.K., Castellini, C.: Introducing a novel training and assessment protocol for pattern matching in myocontrol: case-study of a trans-radial amputee. In: Proceedings of MEC - Myoelectric Control Symposium (2017)

    Google Scholar 

  19. Schürmann, T., Mohler, B.J., Peters, J., Beckerle, P.: How cognitive models of human body experience might push robotics. Front. Neurorobot. 13, 14 (2019)

    Article  Google Scholar 

  20. Haruno, M., Wolpert, D.M., Kawato, M.: Mosaic model for sensorimotor learning and control. Neural Comput. 13(10), 2201–2220 (2001)

    Article  MATH  Google Scholar 

  21. Nguyen-Tuong, D., Peters, J.: Model learning for robot control: a survey. Cogn. Process. 12(4), 319–340 (2011)

    Article  Google Scholar 

  22. Schillaci, G., Hafner, V.V., Lara, B.: Exploration behaviors, body representations, and simulation processes for the development of cognition in artificial agents. Front. Robot. AI 3, 39 (2016)

    Article  Google Scholar 

  23. Schürmann, T., Beckerle, P.: Personalizing human-agent interaction through cognitive models. Front. Psychol. 11, 2299 (2020)

    Article  Google Scholar 

  24. Lanillos, P., Dean-Leon, E., Cheng, G.: Yielding self-perception in robots through sensorimotor contingencies. IEEE Trans. Cogntive Dev. Syst. 9(2), 100–112 (2017)

    Article  Google Scholar 

  25. Asada, M., Hosoda, K., Kuniyoshi, Y., Ishiguro, H., Inui, T., Yoshikawa, Y., Ogino, M., Yoshida, C.: Cognitive developmental robotics: a survey. IEEE Trans. Auton. Ment. Dev. 1(1), 12–34 (2009)

    Article  Google Scholar 

  26. Morse, A.F., De Greeff, J., Belpeame, T., Cangelosi, A.: Epigenetic robotics architecture (ERA). IEEE Trans. Auton. Ment. Dev. 2(4), 325–339 (2010)

    Article  Google Scholar 

  27. Roncone, A., Hoffmann, M., Pattacini, U., Metta, G.: Learning peripersonal space representation through artificial skin for avoidance and reaching with whole body surface. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3366–3373 (2015)

    Google Scholar 

  28. Roncone, A., Hoffmann, M., Pattacini, U., Fadiga, L., Metta, G.: Peripersonal space and margin of safety around the body: learning visuo-tactile associations in a humanoid robot with artificial skin. PloS One 11(10), e0163,713 (2016)

    Google Scholar 

  29. Ulbrich, S., Ruiz de Angulo, V., Asfour, T., Torras, C., Dillmann, R.: Rapid learning of humanoid body schemas with kinematic bézier maps. In: IEEE Interational Conference on Humanoid Robotics (2009)

    Google Scholar 

  30. Lenggenhager, B., Tadi, T., Metzinger, T., Blanke, O.: Video ergo sum: manipulating bodily self-consciousness. Science 317(5841), 1096–1099 (2007)

    Article  Google Scholar 

  31. Aspell, J.E., Lenggenhager, B., Blanke, O.: Keeping in touch with ones self: multisensory mechanisms of self-consciousness. PLoS ONE 4(8), e6488 (2009)

    Article  Google Scholar 

  32. Rohde, M., Di Luca, M., Ernst, M.O.: The rubber hand illusion: feeling of ownership and proprioceptive drift do not go hand in hand. PLoS ONE 6(6) (2011)

    Google Scholar 

  33. Christ, O., Reiner, M.: Perspectives and possible applications of the rubber hand and virtual hand illusion in non-invasive rehabilitation: technological improvements and their consequences. Neurosci. Biobehav. Rev. 44, 33–44 (2014)

    Article  Google Scholar 

  34. Nostadt, N., Abbink, D.A., Christ, O., Beckerle, P.: Embodiment, presence, and their intersections: teleoperation and beyond (submitted). ACM Trans. Hum. Robot Interact. (2020)

    Google Scholar 

  35. Beckerle, P., Kõiva, R., Kirchner, E.A., Bekrater-Bodmann, R., Dosen, S., Christ, O., Abbink, D.A., Castellini, C., Lenggenhager, B.: Feel-good robotics: requirements on touch for embodiment in assistive robotics. Front. Neurorobot. 12, 84 (2018)

    Article  Google Scholar 

  36. Löken, L.S., Wessberg, J., McGlone, F., Olausson, H.: Coding of pleasant touch by unmyelinated afferents in humans. Nat. Neurosci. 12(5), 547 (2009)

    Article  Google Scholar 

  37. Antfolk, C., D’Alonzo, M., Controzzi, M., Lundborg, G., Rosen, B., Sebelius, F., Cipriani, C.: Artificial redirection of sensation from prosthetic fingers to the phantom hand map on transradial amputees: vibrotactile versus mechanotactile sensory feedback. IEEE Trans. Neural Syst. Rehabil. Eng. 21(1), 112–120 (2013)

    Article  Google Scholar 

  38. Schofield, J.S., Evans, K.R., Carey, J.P., Hebert, J.S.: Applications of sensory feedback in motorized upper extremity prosthesis: a review. Expert. Rev. Med. Devices 11(5), 499–511 (2014)

    Article  Google Scholar 

  39. Svensson, P., Wijk, U., Björkman, A., Antfolk, C.: A review of invasive and non-invasive sensory feedback in upper limb prostheses. Expert. Rev. Med. Devices 14(6), 439–447 (2017)

    Article  Google Scholar 

  40. Stephens-Fripp, B., Alici, G., Mutlu, R.: A review of non-invasive sensory feedback methods for transradial prosthetic hands. IEEE Access 6, 6878–6899 (2018)

    Article  Google Scholar 

  41. Hara, M., Pozeg, P., Rognini, G., Higuchi, T., Fukuhara, K., Yamamoto, A., Higuchi, T., Blanke, O., Salomon, R.: Voluntary self-touch increases body ownership. Front. Psychol. 6, 1509 (2015)

    Article  Google Scholar 

  42. Crucianelli, L., Metcalf, N.K., Fotopoulou, A., Jenkinson, P.M.: Bodily pleasure matters: velocity of touch modulates body ownership during the rubber hand illusion. Front. Psychol. 4, 703 (2013)

    Article  Google Scholar 

  43. Crucianelli, L., Krahé, C., Jenkinson, P.M., Fotopoulou, A.K.: Interoceptive ingredients of body ownership: affective touch and cardiac awareness in the rubber hand illusion. Cortex (2017)

    Google Scholar 

  44. van Stralen, H.E., van Zandvoort, M.J.E., Hoppenbrouwers, S.S., Vissers, L.M.G., Kappelle, L.J., Dijkerman, H.C.: Affective touch modulates the rubber hand illusion. Cognition 131(1), 147–158 (2014)

    Article  Google Scholar 

  45. Hassenzahl, M., Tractinsky, N.: User experience-a research agenda. Behav. Inf. Technol. 25(2), 91–97 (2006)

    Article  Google Scholar 

  46. Thüring, M., Mahlke, S.: Usability, aesthetics and emotions in human-technology interaction. Int. J. Psychol. 42(4), 253–264 (2007)

    Article  Google Scholar 

  47. Mahlke, S., Thüring, M.: Studying antecedents of emotional experiences in interactive contexts. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 915–918 (2007)

    Google Scholar 

  48. Hertenstein, M.J., Keltner, D., App, B., Bulleit, B.A., Jaskolka, A.R.: Touch communicates distinct emotions. Emotion 6(3), 528 (2006)

    Article  Google Scholar 

  49. Hertenstein, M.J., Holmes, R., McCullough, M., Keltner, D.: The communication of emotion via touch. Emotion 9(4), 566 (2009)

    Article  Google Scholar 

  50. Dahiya, R.S., Metta, G., Valle, M., Sandini, G.: Tactile sensing - from humans to humanoids. IEEE Trans. Robot. 26(1), 1–20 (2010)

    Article  Google Scholar 

  51. Kim, J., Lee, M., Shim, H.J., Ghaffari, R., Cho, H.R., Son, D., Jung, Y.H., Soh, M., Choi, C., Jung, S., Chu, K., Jeon, D., Lee, S.T., Kim, J.H., Choi, S.H., Hyeon, T., Kim, D.H.: Stretchable silicon nanoribbon electronics for skin prosthesis. Nat. Commun. 5, 5747 (2014)

    Article  Google Scholar 

  52. Raspopovic, S., Capogrosso, M., Petrini, F.M., Bonizzato, M., Rigosa, J., Di Pino, G., Carpaneto, J., Controzzi, M., Boretius, T., Fernandez, E., Granata, G., Oddo, C.M., Citi, L., Ciancio, A.L., Cipriani, C., Carrozza, M.C., Jensen, W., Guglielmelli, E., Stieglitz, T., Rossini, P.M., Micera, S.: Restoring natural sensory feedback in real-time bidirectional hand prostheses. Sci. Transl. Med. 6(222), 222ra19–222ra19 (2014)

    Google Scholar 

  53. Li, K., Fang, Y., Zhou, Y., Liu, H.: Non-invasive stimulation-based tactile sensation for upper-extremity prosthesis: a review. IEEE Sens. J. 17(9), 2625–2635 (2017)

    Google Scholar 

  54. Strbac, M., Isakovic, M., Belic, M., Popovic, I., Simanic, I., Farina, D., Keller, T., Dosen, S.: Short- and long-term learning of feedforward control of a myoelectric prosthesis with sensory feedback by amputees. IEEE Trans. Neural Syst. Rehabil. Eng. (2017)

    Google Scholar 

  55. Dosen, S., Markovic, M., Strbac, M., Belic, M., Popovic, I., Kojic, C., Bijelic, G., Keller, T., Farina, D.: Multichannel electrotactile feedback with spatial and mixed coding for closed-loop control of grasping force in hand prostheses. IEEE Trans. Neural Syst. Rehabil. Eng. 25(3), 183–195 (2017)

    Article  Google Scholar 

  56. Koiva, R., Zenker, M., Schürmann, C., Haschke, R., Ritter, H.J.: A highly sensitive 3D-shaped tactile sensor. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics (2013)

    Google Scholar 

  57. Gallo, S., Santos-Carreras, L., Rognini, G., Hara, M., Yamamoto, A., Higuchi, T.: Towards multimodal haptics for teleoperation: design of a tactile thermal display. In: IEEE International Workshop on Advanced Motion Control (2012)

    Google Scholar 

  58. Pacchierotti, C., Sinclair, S., Solazzi, M., Frisoli, A., Hayward, V., Prattichizzo, D.: Wearable haptic systems for the fingertip and the hand: taxonomy, review, and perspectives. IEEE Trans. Haptics 10(4), 580–600 (2017)

    Article  Google Scholar 

  59. Aggarwal, A., Kampmann, P., Lemburg, J., Kirchner, F.: Haptic object recognition in underwater and deep-sea environments. J. Field Robot. 32(1), 167–185 (2015)

    Article  Google Scholar 

  60. Witteveen, H.J.B., Rietman, H.S., Veltink, P.H.: Vibrotactile grasping force and hand aperture feedback for myoelectric forearm prosthesis users. Prosthet. Orthot. Int. 39(3), 204–212 (2015)

    Article  Google Scholar 

  61. Shokur, S., Gallo, S., Moioli, R.C., Donati, A.R.C., Morya, E., Bleuler, H., Nicolelis, M.A.L.: Assimilation of virtual legs and perception of floor texture by complete paraplegic patients receiving artificial tactile feedback. Sci. Rep. 6, 32,293 (2016)

    Google Scholar 

  62. Culbertson, H., Nunez, C.M., Israr, A., Lau, F., Abnousi, F., Okamura, A.M.: A social haptic device to create continuous lateral motion using sequential normal indentation. In: IEEE Haptics Symposium, pp. 32–39 (2018)

    Google Scholar 

  63. Ham, R., Cotton, L.T.: Limb Amputation: From Aetiology to Rehabilitation. Springer (2013)

    Google Scholar 

  64. Bremner, A.J., Spence, C.: The development of tactile perception. In: Advances in Child Development and Behavior, vol. 52, pp. 227–268. Elsevier (2017)

    Google Scholar 

  65. Dieguez, S., Mervier, M.R., Newby, N., Blanke, O.: Feeling numbness for someone else’s finger. Curr. Biol. 19(24), R1108–R1109 (2009)

    Article  Google Scholar 

  66. Huynh, T.V., Scherf, A., Bittner, A., Saetta, G., Lenggenhager, B., Beckerle, P.: Design of a wearable robotic hand to investigate multisensory illusions and the bodily self of humans (accepted). In: International Symposium on Robotics (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Philipp Beckerle .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Beckerle, P. (2021). Research Outlook. In: Human-Robot Body Experience. Springer Series on Touch and Haptic Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-38688-7_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-38688-7_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38687-0

  • Online ISBN: 978-3-030-38688-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics