Skip to main content

Development of Direct-printed Tactile Sensors for Gripper Control through Contact and Slip Detection

International Journal of Control, Automation and Systems volume 16, pages 929–936 (2018)Cite this article

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Abstract

This work demonstrates the use of printed tactile sensors for detection of contact location and slip in a robot gripper. Research and development of robots for behaviors similar to those of humans are being conducted by many institutions. For these robot systems, flexible tactile sensors imitating human tactile senses have been developed and applied to robots. The sensors used in this work were fabricated through a direct-print process using a multi-walled carbon nanotube (MWCNT)/polymer composite. These sensors are a resistance type and were characterized by detecting changes in resistance of MWCNT networks within the composite in response to external forces. With tactile sensors attached to gripper fingers, signals generated when the gripper grasped objects were analyzed and the resulting information was used for robot gripper control.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

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

References

  1. A. Joubair, L. F. Zhao, P. Bigras, and I. A. Bonev, “Use of a force-torque sensor for self-calibration of a 6-DOF medical robot,” Sensors, vol. 16, no. 6, p. 798, 2016.

    Article  Google Scholar 

  2. D. Wu, T. Chen, and A. Li, “A high precision approach to calibrate a structured light vision sensor in a robot-based three-dimensional measurement system,” Sensors, vol. 16, no. 9, p. 1388, 2016. [click]

    Article  Google Scholar 

  3. R. S. Dahiya, and M. Valle, Tactile Sensing for Robotic Applications, INTECH Open Access Publisher, 2008.

    Google Scholar 

  4. F. Alonso-Martín, M. Malfaz, J. Sequeira, J. F. Gorostiza, and M. A. Salichs, “A multimodal emotion detection system during human–robot interaction,” Sensors, vol. 13, no. 11, pp. 15549–15581, 2013. [click]

    Article  Google Scholar 

  5. Y. Jung, D.-G. Lee, J. Park, H. Ko, and H. Lim, “Piezoresistive tactile sensor discriminating multidirectional forces,” Sensors, vol. 15, no. 10, pp. 25463–25473, 2015. [click]

    Article  Google Scholar 

  6. J. W. Morley, A. W. Goodwin, and I. Darian-Smith, “Tactile discrimination of gratings,” Experimental Brain Research, vol. 49, no. 2, pp. 291–299, 1983.

    Article  Google Scholar 

  7. N. Sato, S. Shigematsu, H. Morimura, M. Yano, K. Kudou, T. Kamei, and K. Machida, “Novel surface structure and its fabrication process for MEMS fingerprint sensor,” IEEE Transactions on Electron Devices, vol. 52, no. 5, pp. 1026–1032, 2005.

    Article  Google Scholar 

  8. T. Someya, Y. Kato, T. Sekitani, S. Iba, Y. Noguchi, Y. Murase, H. Kawaguchi, and T. Sakurai, “Conformable, flexible, large-area networks of pressure and thermal sensors with organic transistor active matrixes,” Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 35, pp. 12321–12325, 2005. [click]

    Article  Google Scholar 

  9. G. S. Kim, and H. J. Shin, “Development of intelligent robot’s hand with three-axis finger force sensors for intelligent robot,” Journal of Institute of Control, Robotics and Systems, vol. 15, no. 3, pp. 300–305, 2009.

    Article  Google Scholar 

  10. H. Liu, F. Sun, D. Guo, B. Fang, and Z. Peng, “Structured output-associated dictionary learning for haptic understanding,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 7, pp. 1567–1574, 2017.

    Google Scholar 

  11. H. Liu, J. Qin, F. Sun, and D. Guo, “Extreme kernel sparse learning for tactile object recognition,” IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4509–4520, Dec. 2017. [click]

    Article  Google Scholar 

  12. M. Vatani, Y. Lu, K.-S. Lee, H.-C. Kim, and J.-W. Choi, “Direct-write stretchable sensors using single-walled carbon nanotube/polymer matrix,” Journal of Electronic Packaging, vol. 135, no. 1, pp. 011009, 2013.

    Article  Google Scholar 

  13. M. Vatani, E. D. Engeberg, and J.-W. Choi, “Force and slip detection with direct-write compliant tactile sensors using multi-walled carbon nanotube/polymer composites,” Sensors and Actuators A: Physical, vol. 195, pp. 90–97, 2013. 13. [click]

    Article  Google Scholar 

  14. M. Vatani, E. D. Engeberg, and J. W. Choi, “Detection of the position, direction and speed of sliding contact with a multi-layer compliant tactile sensor fabricated using directprint technology,” Smart Materials and Structures, vol. 23, no. 9, pp. 1–11, 2014.

    Article  Google Scholar 

  15. M. Vatani, Y. Lu, E. D. Engeberg, and J. W. Choi, “Combined 3D printing technologies and material for fabrication of tactile sensors,” International Journal of Precision Engineering and Manufacturing, vol. 16, no. 7, pp. 1375–1383, 2015. [click]

    Article  Google Scholar 

  16. M. Vatani, E. D. Engeberg, and J.-W. Choi, “Conformal direct-print of piezoresistive polymer/nanocomposites for compliant multi-layer tactile sensors,” Additive Manufacturing, vol. 7, pp. 73–82, 2015. [click]

    Article  Google Scholar 

  17. I. Akita, and M. Ishida, “A 0.06 mm2 14nV/Hz chopper instrumentation amplifier with automatic differential-pair matching,” Proc. of IEEE International Solid-State Circuits Conference Digest of Technical Papers (ISSCC), pp. 178–179, 2013. [click]

    Google Scholar 

  18. E. D. Engeberg, and S. G. Meek, “Adaptive sliding mode control for prosthetic hands to simultaneously prevent slip and minimize deformation of grasped objects,” IEEE/ASME Transactions on Mechatronics, vol. 18, no. 1, pp. 376–385, 2013. [click]

    Article  Google Scholar 

  19. L. D. Harmon, “Automated tactile sensing,” The International Journal of Robotics Research, vol. 1, no. 2, pp. 3–32, 1982.

    Article  Google Scholar 

  20. R. S. Dahiya, and M. Valle, Robotic Tactile Sensing: Technologies and System, Springer Science & Business Media, 2012.

    Google Scholar 

  21. H. J. Lee, J.-K. Ryu, J. Kim, Y. J. Shin, K.-S. Kim, and S. Kim, “Design of modular gripper for explosive ordinance disposal robot manipulator based on modified dual-mode twisting actuation,” International Journal of Control, Automation and Systems, vol. 14, no. 5, pp. 1322–1330, 2016. [click]

    Article  Google Scholar 

  22. T. C. Phung, M. J. Kim, H. Moon, J. C. Koo, and H. R. Choi, “Exploration of local surface geometry with minimum number of contact points and surface normal information,” International Journal of Control, Automation and Systems, vol. 10, no. 2, pp. 383–395, 2012. [click]

    Article  Google Scholar 

  23. S. Lee and P. Y. Oh, “Sensor information analysis for a humanoid robot,” International Journal of Control, Automation, and Systems, vol. 13, no. 1, pp. 175, 2015. [click]

    Article  Google Scholar 

  24. A. Cavallo, G. De Maria, C. Natale, and S. Pirozzi, “Slipping detection and avoidance based on Kalman filter,” Mechatronics, vol. 24, no. 5, pp. 489–499, 2014.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Pusan National University, Busandaekak-ro, Geumjeong-gu, Busan, 46241, Korea

    Ju-Kyoung Lee & Suk Lee

  2. Department of Control and Instrumentation Engineering, Pukyung National University, 45, Yongso-ro, Nam-Gu, Busan, 48513, Korea

    Hyun-Hee Kim & Kyung-Chang Lee

  3. Department of Mechanical Engineering, The University of Akron, 244 Sumner Street, Akron, Ohio, 44325, USA

    Jae-Won Choi

Authors
  1. Ju-Kyoung Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hyun-Hee Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jae-Won Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kyung-Chang Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Suk Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Suk Lee.

Additional information

Recommended by Associate Editor Huaping Liu under the direction of Editor Fuchun Sun. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education(NRF-2016R1A6A3A11931489).

Ju-Kyoung Lee is a Ph.D. candidate in Mechanical Engineering at the Pusan National University, Busan, Korea. His research interests are industrial network and robotics, sensor network and signal processing, and 3D printed tactile sensors and their applications.

Hyun-Hee Kim received her Ph.D. degree from Pusan National University, Busan, Korea, in 2010. She is a Research Fellow in the Department of Control and Instrumentation Engineering, Pukyong National University, Busan, Korea. Her research interests are industrial networks, home networks, wireless networks, and networked control systems.

Jae-Won Choi is an Associate Professor in the Department of Mechanical Engineering at The University of Akron (UA). Prior to joining the UA, he spent three years for Micro/Macro Additive Manufacturing in the W.M. Keck Center for 3D Innovation at the University of Texas at El Paso (UTEP). His B.S., M.S. and Ph.D. degrees were obtained from Pusan National University (PNU) in South Korea, in 1999, 2001, and 2007, respectively. His research interests include advanced additive manufacturing, 3D printing of smart structures, low-cost 3D metal printing, and bio fabrication.

Kyung-Chang Lee received his Ph.D. degree from Pusan National University, Busan, Korea, in 2003. He is a professor in the Department of Control and Instrumentation Engineering, Pukyong National University, Busan, Korea. His research interests are embedded network system, industrial network, robotic network, invehicle network, home network, wireless sensor network, and networked control system.

Suk Lee received his Ph.D. degree from The Pennsylvania State University, University Park, in 1990. He is a professor in the School of Mechanical Engineering, Pusan National University, Busan, Korea. His research interests are industrial network, in-vehicle network, and home network.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lee, JK., Kim, HH., Choi, JW. et al. Development of Direct-printed Tactile Sensors for Gripper Control through Contact and Slip Detection. Int. J. Control Autom. Syst. 16, 929–936 (2018). https://doi.org/10.1007/s12555-017-0151-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-017-0151-x

Keywords

  • Direct-print
  • multi-walled carbon nanotube
  • robot gripper
  • signal processing
  • slip detection
  • tactile sensor